predict.DArch: Forward-propagate data.

Description Usage Arguments Value See Also Examples

View source: R/predict.R

Description

Forward-propagate given data through the deep neural network.

Usage

1
2
3
## S3 method for class 'DArch'
predict(object, ..., newdata = NULL, type = "raw",
  inputLayer = 1, outputLayer = 0)

Arguments

object

DArch instance

...

Further parameters, if newdata is NULL, the first unnamed parameter will be used for newdata instead.

newdata

New data to predict, NULL to return latest network output

type

Output type, one of: raw, bin, class, or character. raw returns the layer output, bin returns 1 for every layer output >0.5, 0 otherwise, and class returns 1 for the output unit with the highest activation, otherwise 0. Additionally, when using class, class labels are returned when available. character is the same as class, except using character vectors instead of factors.

inputLayer

Layer number (> 0). The data given in newdata will be fed into this layer. Note that absolute numbers count from the input layer, i.e. for a network with three layers, 1 would indicate the input layer.

outputLayer

Layer number (if > 0) or offset (if <= 0) relative to the last layer. The output of the given layer is returned. Note that absolute numbers count from the input layer, i.e. for a network with three layers, 1 would indicate the input layer.

Value

Vector or matrix of networks outputs, output type depending on the type parameter.

See Also

Other darch interface functions: darchBench, darchTest, darch, plot.DArch, print.DArch

Examples

1
2
3
4
5
6
## Not run: 
data(iris)
model <- darch(Species ~ ., iris, retainData = T)
predict(model)

## End(Not run)

Example output

INFO [2018-12-01 15:46:06] The current log level is: INFO
INFO [2018-12-01 15:46:06] Start initial caret pre-processing.
INFO [2018-12-01 15:46:06] Converting non-numeric columns in data (if any)...
INFO [2018-12-01 15:46:06] Converting non-numeric columns in targets (if any)...
INFO [2018-12-01 15:46:06] Dependent factor "Species" converted to 3 new variables (1-of-n coding)
INFO [2018-12-01 15:46:06] The current log level is: INFO
INFO [2018-12-01 15:46:06] Using CPU matrix multiplication.
WARN [2018-12-01 15:46:06] No vector given for "layers" parameter, constructing shallow network with one hidden layer of 10 neurons.
INFO [2018-12-01 15:46:06] Creating and configuring new DArch instance
INFO [2018-12-01 15:46:06] Constructing a network with 3 layers (4, 10, 3 neurons).
INFO [2018-12-01 15:46:06] Generating RBMs.
INFO [2018-12-01 15:46:06] Constructing new RBM instance with 4 visible and 10 hidden units.
INFO [2018-12-01 15:46:06] Constructing new RBM instance with 10 visible and 3 hidden units.
INFO [2018-12-01 15:46:06] DArch instance ready for training, here is a summary of its configuration:
INFO [2018-12-01 15:46:06] Global parameters:
INFO [2018-12-01 15:46:06] Layers parameter was 10, resulted in network with 3 layers and 4, 10, 3 neurons
INFO [2018-12-01 15:46:06] The weights for the layers were generated with "generateWeightsGlorotUniform"
INFO [2018-12-01 15:46:06] Additionally, the following parameters were used for weight generation:
INFO [2018-12-01 15:46:06] [weights] Parameter weights.max is 0.1
INFO [2018-12-01 15:46:06] [weights] Parameter weights.min is -0.1
INFO [2018-12-01 15:46:06] [weights] Parameter weights.mean is 0
INFO [2018-12-01 15:46:06] [weights] Parameter weights.sd is 0.01
INFO [2018-12-01 15:46:06] Weight normalization is disabled
INFO [2018-12-01 15:46:06] Bootstrapping is disabled
INFO [2018-12-01 15:46:06] Train data are shuffled before each epoch
INFO [2018-12-01 15:46:06] Autosaving is disabled
INFO [2018-12-01 15:46:06] Using CPU for matrix multiplication
INFO [2018-12-01 15:46:06] Pre-processing parameters:
INFO [2018-12-01 15:46:06] [preProc] Parameter preProc.factorToNumeric is FALSE
INFO [2018-12-01 15:46:06] [preProc] Parameter preProc.factorToNumeric.targets is FALSE
INFO [2018-12-01 15:46:06] [preProc] Parameter preProc.fullRank is TRUE
INFO [2018-12-01 15:46:06] [preProc] Parameter preProc.fullRank.targets is FALSE
INFO [2018-12-01 15:46:06] [preProc] Parameter preProc.orderedToFactor.targets is TRUE
INFO [2018-12-01 15:46:06] [preProc] Parameter preProc.targets is FALSE
INFO [2018-12-01 15:46:06] Caret pre-processing is disabled
INFO [2018-12-01 15:46:06] Pre-training parameters:
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.allData is FALSE
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.batchSize is 1
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.consecutive is TRUE
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.errorFunction is "mseError"
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.finalMomentum is 0.9
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.initialMomentum is 0.5
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.lastLayer is 0
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.learnRate is 1
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.learnRateScale is 1
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.momentumRampLength is 1
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.numCD is 1
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.numEpochs is 0
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.unitFunction is "sigmoidUnitRbm"
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.updateFunction is "rbmUpdate"
INFO [2018-12-01 15:46:06] [preTrain] Parameter rbm.weightDecay is 2e-04
INFO [2018-12-01 15:46:06] The selected RBMs have been trained for 0 epochs
INFO [2018-12-01 15:46:06] Fine-tuning parameters:
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.batchSize is 1
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.dither is FALSE
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.dropout is 0
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.dropout.dropConnect is FALSE
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.dropout.momentMatching is 0
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.dropout.oneMaskPerEpoch is FALSE
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.elu.alpha is 1
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.errorFunction is "crossEntropyError"
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.finalMomentum is 0.9
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.fineTuneFunction is "backpropagation"
INFO [2018-12-01 15:46:06] [backprop] Using backpropagation for fine-tuning
INFO [2018-12-01 15:46:06] [backprop] Parameter bp.learnRate is c(1, 1)
INFO [2018-12-01 15:46:06] [backprop] Parameter bp.learnRateScale is 1
INFO [2018-12-01 15:46:06] [backprop] See ?backpropagation for documentation
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.initialMomentum is 0.5
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.isClass is TRUE
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.maxout.poolSize is 2
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.maxout.unitFunction is "linearUnit"
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.momentumRampLength is 1
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.nesterovMomentum is TRUE
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.numEpochs is 100
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.returnBestModel is TRUE
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.returnBestModel.validationErrorFactor is 0.632120558828558
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.stopClassErr is -Inf
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.stopErr is -Inf
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.stopValidClassErr is -Inf
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.stopValidErr is -Inf
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.trainLayers is c(TRUE, TRUE)
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.unitFunction is "sigmoidUnit"
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.weightDecay is 0
INFO [2018-12-01 15:46:06] [fineTune] Parameter darch.weightUpdateFunction is "weightDecayWeightUpdate"
INFO [2018-12-01 15:46:06] The network has been fine-tuned for 0 epochs
INFO [2018-12-01 15:46:06] Training set consists of 150 samples.
INFO [2018-12-01 15:46:06] Start deep architecture fine-tuning for 100 epochs
INFO [2018-12-01 15:46:06] Number of Batches: 150 (batch size 1)
INFO [2018-12-01 15:46:06] Epoch:   1 of 100
INFO [2018-12-01 15:46:06] Classification error on Train set: 41.33% (62/150)
INFO [2018-12-01 15:46:06] Train set Cross Entropy error: 1.176
INFO [2018-12-01 15:46:06] Finished epoch   1 of 100 after 0.122 secs (1251 patterns/sec)
INFO [2018-12-01 15:46:06] Epoch:   2 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 33.33% (50/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 1.118
INFO [2018-12-01 15:46:07] Finished epoch   2 of 100 after 0.0543 secs (2864 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:   3 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 20% (30/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.908
INFO [2018-12-01 15:46:07] Finished epoch   3 of 100 after 0.0457 secs (3428 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:   4 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 8.67% (13/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.798
INFO [2018-12-01 15:46:07] Finished epoch   4 of 100 after 0.0437 secs (3597 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:   5 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 14% (21/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.747
INFO [2018-12-01 15:46:07] Finished epoch   5 of 100 after 0.0453 secs (3487 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:   6 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 32.67% (49/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 1.167
INFO [2018-12-01 15:46:07] Finished epoch   6 of 100 after 0.0414 secs (3807 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:   7 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 19.33% (29/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.773
INFO [2018-12-01 15:46:07] Finished epoch   7 of 100 after 0.0454 secs (3447 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:   8 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 16.67% (25/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.695
INFO [2018-12-01 15:46:07] Finished epoch   8 of 100 after 0.0409 secs (3836 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:   9 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 16.67% (25/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.692
INFO [2018-12-01 15:46:07] Finished epoch   9 of 100 after 0.0445 secs (3512 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  10 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 9.33% (14/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.509
INFO [2018-12-01 15:46:07] Finished epoch  10 of 100 after 0.0409 secs (3843 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  11 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 8% (12/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.476
INFO [2018-12-01 15:46:07] Finished epoch  11 of 100 after 0.0445 secs (3511 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  12 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 24% (36/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.866
INFO [2018-12-01 15:46:07] Finished epoch  12 of 100 after 0.041 secs (3859 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  13 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 8% (12/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.814
INFO [2018-12-01 15:46:07] Finished epoch  13 of 100 after 0.0437 secs (3571 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  14 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 33.33% (50/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 1.554
INFO [2018-12-01 15:46:07] Finished epoch  14 of 100 after 0.0402 secs (3904 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  15 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 5.33% (8/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.396
INFO [2018-12-01 15:46:07] Finished epoch  15 of 100 after 0.0438 secs (3576 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  16 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 31.33% (47/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 1.645
INFO [2018-12-01 15:46:07] Finished epoch  16 of 100 after 0.0406 secs (3883 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  17 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 30% (45/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 1.395
INFO [2018-12-01 15:46:07] Finished epoch  17 of 100 after 0.0454 secs (3433 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  18 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 4.67% (7/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.462
INFO [2018-12-01 15:46:07] Finished epoch  18 of 100 after 0.0401 secs (3922 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  19 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 18% (27/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.823
INFO [2018-12-01 15:46:07] Finished epoch  19 of 100 after 0.0446 secs (3499 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  20 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 6% (9/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.355
INFO [2018-12-01 15:46:07] Finished epoch  20 of 100 after 0.0405 secs (3884 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  21 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.263
INFO [2018-12-01 15:46:07] Finished epoch  21 of 100 after 0.0455 secs (3430 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  22 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 4.67% (7/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.302
INFO [2018-12-01 15:46:07] Finished epoch  22 of 100 after 0.0409 secs (3842 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  23 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 2% (3/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.238
INFO [2018-12-01 15:46:07] Finished epoch  23 of 100 after 0.0446 secs (3500 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  24 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 16.67% (25/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.690
INFO [2018-12-01 15:46:07] Finished epoch  24 of 100 after 0.04 secs (3933 patterns/sec)
INFO [2018-12-01 15:46:07] Epoch:  25 of 100
INFO [2018-12-01 15:46:07] Classification error on Train set: 4% (6/150)
INFO [2018-12-01 15:46:07] Train set Cross Entropy error: 0.283
INFO [2018-12-01 15:46:08] Finished epoch  25 of 100 after 0.0451 secs (3465 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  26 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 9.33% (14/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.539
INFO [2018-12-01 15:46:08] Finished epoch  26 of 100 after 0.0397 secs (3966 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  27 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 1.33% (2/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.204
INFO [2018-12-01 15:46:08] Finished epoch  27 of 100 after 0.0446 secs (3514 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  28 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 5.33% (8/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.316
INFO [2018-12-01 15:46:08] Finished epoch  28 of 100 after 0.0401 secs (3928 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  29 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 7.33% (11/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.342
INFO [2018-12-01 15:46:08] Finished epoch  29 of 100 after 0.0453 secs (3446 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  30 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 15.33% (23/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.617
INFO [2018-12-01 15:46:08] Finished epoch  30 of 100 after 0.0413 secs (3828 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  31 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 4% (6/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.252
INFO [2018-12-01 15:46:08] Finished epoch  31 of 100 after 0.0453 secs (3445 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  32 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 6% (9/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.340
INFO [2018-12-01 15:46:08] Finished epoch  32 of 100 after 0.0402 secs (3909 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  33 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.308
INFO [2018-12-01 15:46:08] Finished epoch  33 of 100 after 0.0446 secs (3876 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  34 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 6.67% (10/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.308
INFO [2018-12-01 15:46:08] Finished epoch  34 of 100 after 0.0408 secs (3847 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  35 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 2% (3/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.177
INFO [2018-12-01 15:46:08] Finished epoch  35 of 100 after 0.041 secs (3847 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  36 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 5.33% (8/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.228
INFO [2018-12-01 15:46:08] Finished epoch  36 of 100 after 0.0466 secs (3348 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  37 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 2.67% (4/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.207
INFO [2018-12-01 15:46:08] Finished epoch  37 of 100 after 0.0401 secs (3916 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  38 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 6.67% (10/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.254
INFO [2018-12-01 15:46:08] Finished epoch  38 of 100 after 0.0463 secs (3370 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  39 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 4% (6/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.224
INFO [2018-12-01 15:46:08] Finished epoch  39 of 100 after 0.0414 secs (3797 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  40 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 2% (3/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.217
INFO [2018-12-01 15:46:08] Finished epoch  40 of 100 after 0.0437 secs (3576 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  41 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 5.33% (8/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.287
INFO [2018-12-01 15:46:08] Finished epoch  41 of 100 after 0.0406 secs (3881 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  42 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 5.33% (8/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.228
INFO [2018-12-01 15:46:08] Finished epoch  42 of 100 after 0.0445 secs (3522 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  43 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 6.67% (10/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.379
INFO [2018-12-01 15:46:08] Finished epoch  43 of 100 after 0.0435 secs (3602 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  44 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 5.33% (8/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.235
INFO [2018-12-01 15:46:08] Finished epoch  44 of 100 after 0.0456 secs (3422 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  45 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 4.67% (7/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.257
INFO [2018-12-01 15:46:08] Finished epoch  45 of 100 after 0.0402 secs (3907 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  46 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 6.67% (10/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.338
INFO [2018-12-01 15:46:08] Finished epoch  46 of 100 after 0.0445 secs (3515 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  47 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 4% (6/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.463
INFO [2018-12-01 15:46:08] Finished epoch  47 of 100 after 0.0405 secs (3896 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  48 of 100
INFO [2018-12-01 15:46:08] Classification error on Train set: 8.67% (13/150)
INFO [2018-12-01 15:46:08] Train set Cross Entropy error: 0.446
INFO [2018-12-01 15:46:08] Finished epoch  48 of 100 after 0.0441 secs (3546 patterns/sec)
INFO [2018-12-01 15:46:08] Epoch:  49 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 8.67% (13/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.334
INFO [2018-12-01 15:46:09] Finished epoch  49 of 100 after 0.041 secs (3836 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  50 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 15.33% (23/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.710
INFO [2018-12-01 15:46:09] Finished epoch  50 of 100 after 0.0452 secs (3460 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  51 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 31.33% (47/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 1.056
INFO [2018-12-01 15:46:09] Finished epoch  51 of 100 after 0.0409 secs (3864 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  52 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 14% (21/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.679
INFO [2018-12-01 15:46:09] Finished epoch  52 of 100 after 0.0443 secs (3526 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  53 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 18% (27/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.813
INFO [2018-12-01 15:46:09] Finished epoch  53 of 100 after 0.0402 secs (3919 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  54 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 4% (6/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.254
INFO [2018-12-01 15:46:09] Finished epoch  54 of 100 after 0.045 secs (3469 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  55 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 29.33% (44/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 1.346
INFO [2018-12-01 15:46:09] Finished epoch  55 of 100 after 0.0423 secs (3708 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  56 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.268
INFO [2018-12-01 15:46:09] Finished epoch  56 of 100 after 0.0465 secs (3350 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  57 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.200
INFO [2018-12-01 15:46:09] Finished epoch  57 of 100 after 0.0399 secs (3947 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  58 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 8% (12/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.407
INFO [2018-12-01 15:46:09] Finished epoch  58 of 100 after 0.0457 secs (3430 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  59 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 5.33% (8/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.319
INFO [2018-12-01 15:46:09] Finished epoch  59 of 100 after 0.0401 secs (3931 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  60 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 19.33% (29/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.775
INFO [2018-12-01 15:46:09] Finished epoch  60 of 100 after 0.0442 secs (3539 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  61 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.263
INFO [2018-12-01 15:46:09] Finished epoch  61 of 100 after 0.0394 secs (4005 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  62 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 6% (9/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.250
INFO [2018-12-01 15:46:09] Finished epoch  62 of 100 after 0.0445 secs (3518 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  63 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.227
INFO [2018-12-01 15:46:09] Finished epoch  63 of 100 after 0.0399 secs (3940 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  64 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 2% (3/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.159
INFO [2018-12-01 15:46:09] Finished epoch  64 of 100 after 0.0448 secs (3878 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  65 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.187
INFO [2018-12-01 15:46:09] Finished epoch  65 of 100 after 0.0401 secs (3932 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  66 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 14.67% (22/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.808
INFO [2018-12-01 15:46:09] Finished epoch  66 of 100 after 0.0407 secs (3865 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  67 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 5.33% (8/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.275
INFO [2018-12-01 15:46:09] Finished epoch  67 of 100 after 0.0452 secs (3455 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  68 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 2% (3/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.207
INFO [2018-12-01 15:46:09] Finished epoch  68 of 100 after 0.0411 secs (3813 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  69 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 2.67% (4/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.177
INFO [2018-12-01 15:46:09] Finished epoch  69 of 100 after 0.0459 secs (3438 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  70 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.243
INFO [2018-12-01 15:46:09] Finished epoch  70 of 100 after 0.0414 secs (3788 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  71 of 100
INFO [2018-12-01 15:46:09] Classification error on Train set: 8% (12/150)
INFO [2018-12-01 15:46:09] Train set Cross Entropy error: 0.347
INFO [2018-12-01 15:46:09] Finished epoch  71 of 100 after 0.0445 secs (3518 patterns/sec)
INFO [2018-12-01 15:46:09] Epoch:  72 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 4.67% (7/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.286
INFO [2018-12-01 15:46:10] Finished epoch  72 of 100 after 0.041 secs (3828 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  73 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 2.67% (4/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.196
INFO [2018-12-01 15:46:10] Finished epoch  73 of 100 after 0.0439 secs (3558 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  74 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 6.67% (10/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.357
INFO [2018-12-01 15:46:10] Finished epoch  74 of 100 after 0.0428 secs (3664 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  75 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 2% (3/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.213
INFO [2018-12-01 15:46:10] Finished epoch  75 of 100 after 0.0446 secs (3505 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  76 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 2% (3/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.183
INFO [2018-12-01 15:46:10] Finished epoch  76 of 100 after 0.0406 secs (3875 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  77 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.228
INFO [2018-12-01 15:46:10] Finished epoch  77 of 100 after 0.0445 secs (3515 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  78 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 8% (12/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.418
INFO [2018-12-01 15:46:10] Finished epoch  78 of 100 after 0.0403 secs (3903 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  79 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 8% (12/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.257
INFO [2018-12-01 15:46:10] Finished epoch  79 of 100 after 0.044 secs (3545 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  80 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 1.33% (2/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.224
INFO [2018-12-01 15:46:10] Finished epoch  80 of 100 after 0.0402 secs (3917 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  81 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 4.67% (7/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.465
INFO [2018-12-01 15:46:10] Finished epoch  81 of 100 after 0.0454 secs (3448 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  82 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 5.33% (8/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.321
INFO [2018-12-01 15:46:10] Finished epoch  82 of 100 after 0.0409 secs (3878 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  83 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 6.67% (10/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.345
INFO [2018-12-01 15:46:10] Finished epoch  83 of 100 after 0.0471 secs (3307 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  84 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 2% (3/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.178
INFO [2018-12-01 15:46:10] Finished epoch  84 of 100 after 0.0401 secs (3927 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  85 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 8% (12/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.427
INFO [2018-12-01 15:46:10] Finished epoch  85 of 100 after 0.0448 secs (3493 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  86 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 16% (24/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.559
INFO [2018-12-01 15:46:10] Finished epoch  86 of 100 after 0.0404 secs (3890 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  87 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 2.67% (4/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.180
INFO [2018-12-01 15:46:10] Finished epoch  87 of 100 after 0.0445 secs (3509 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  88 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 4% (6/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.355
INFO [2018-12-01 15:46:10] Finished epoch  88 of 100 after 0.0401 secs (3921 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  89 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.253
INFO [2018-12-01 15:46:10] Finished epoch  89 of 100 after 0.0448 secs (3486 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  90 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 6.67% (10/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.372
INFO [2018-12-01 15:46:10] Finished epoch  90 of 100 after 0.0402 secs (3917 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  91 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 2% (3/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.150
INFO [2018-12-01 15:46:10] Finished epoch  91 of 100 after 0.0486 secs (3211 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  92 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 4.67% (7/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.283
INFO [2018-12-01 15:46:10] Finished epoch  92 of 100 after 0.0397 secs (3957 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  93 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.241
INFO [2018-12-01 15:46:10] Finished epoch  93 of 100 after 0.0441 secs (3550 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  94 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 3.33% (5/150)
INFO [2018-12-01 15:46:10] Train set Cross Entropy error: 0.211
INFO [2018-12-01 15:46:10] Finished epoch  94 of 100 after 0.0399 secs (3945 patterns/sec)
INFO [2018-12-01 15:46:10] Epoch:  95 of 100
INFO [2018-12-01 15:46:10] Classification error on Train set: 5.33% (8/150)
INFO [2018-12-01 15:46:11] Train set Cross Entropy error: 0.221
INFO [2018-12-01 15:46:11] Finished epoch  95 of 100 after 0.046 secs (3424 patterns/sec)
INFO [2018-12-01 15:46:11] Epoch:  96 of 100
INFO [2018-12-01 15:46:11] Classification error on Train set: 2.67% (4/150)
INFO [2018-12-01 15:46:11] Train set Cross Entropy error: 0.144
INFO [2018-12-01 15:46:11] Finished epoch  96 of 100 after 0.0434 secs (3605 patterns/sec)
INFO [2018-12-01 15:46:11] Epoch:  97 of 100
INFO [2018-12-01 15:46:11] Classification error on Train set: 2% (3/150)
INFO [2018-12-01 15:46:11] Train set Cross Entropy error: 0.162
INFO [2018-12-01 15:46:11] Finished epoch  97 of 100 after 0.0411 secs (3840 patterns/sec)
INFO [2018-12-01 15:46:11] Epoch:  98 of 100
INFO [2018-12-01 15:46:11] Classification error on Train set: 2% (3/150)
INFO [2018-12-01 15:46:11] Train set Cross Entropy error: 0.176
INFO [2018-12-01 15:46:11] Finished epoch  98 of 100 after 0.0441 secs (3544 patterns/sec)
INFO [2018-12-01 15:46:11] Epoch:  99 of 100
INFO [2018-12-01 15:46:11] Classification error on Train set: 10% (15/150)
INFO [2018-12-01 15:46:11] Train set Cross Entropy error: 0.517
INFO [2018-12-01 15:46:11] Finished epoch  99 of 100 after 0.041 secs (3830 patterns/sec)
INFO [2018-12-01 15:46:11] Epoch: 100 of 100
INFO [2018-12-01 15:46:11] Classification error on Train set: 20.67% (31/150)
INFO [2018-12-01 15:46:11] Train set Cross Entropy error: 0.860
INFO [2018-12-01 15:46:11] Finished epoch 100 of 100 after 0.0456 secs (3420 patterns/sec)
INFO [2018-12-01 15:46:11] Classification error on Train set (best model): 1.33% (2/150)
INFO [2018-12-01 15:46:11] Train set (best model) Cross Entropy error: 0.204
INFO [2018-12-01 15:46:11] Best model was found after epoch 27
INFO [2018-12-01 15:46:11] Fine-tuning finished after 4.402 secs
               [,1]       [,2]         [,3]
  [1,] 0.9815246085 0.02789029 0.0003240608
  [2,] 0.9784465364 0.03213947 0.0003585835
  [3,] 0.9805187044 0.02894629 0.0003359072
  [4,] 0.9769797943 0.03320844 0.0003742539
  [5,] 0.9817066473 0.02741898 0.0003219309
  [6,] 0.9805402694 0.02808003 0.0003338661
  [7,] 0.9799318528 0.02875301 0.0003419080
  [8,] 0.9802624594 0.02932799 0.0003381508
  [9,] 0.9758643721 0.03464981 0.0003867092
 [10,] 0.9787291376 0.03190984 0.0003555046
 [11,] 0.9818888093 0.02757716 0.0003196936
 [12,] 0.9787819213 0.03073725 0.0003542986
 [13,] 0.9790417621 0.03154288 0.0003523972
 [14,] 0.9810910456 0.02833720 0.0003306900
 [15,] 0.9833071592 0.02649967 0.0003037400
 [16,] 0.9827001261 0.02587937 0.0003096469
 [17,] 0.9824511548 0.02635248 0.0003129365
 [18,] 0.9811232604 0.02805232 0.0003283438
 [19,] 0.9810276926 0.02846147 0.0003289555
 [20,] 0.9814988486 0.02716348 0.0003237225
 [21,] 0.9787887583 0.03173462 0.0003540392
 [22,] 0.9807530904 0.02778883 0.0003318966
 [23,] 0.9827420985 0.02611837 0.0003109057
 [24,] 0.9726983662 0.03770563 0.0004165002
 [25,] 0.9722338737 0.03870163 0.0004216704
 [26,] 0.9747525439 0.03707503 0.0003970992
 [27,] 0.9774929749 0.03189822 0.0003675253
 [28,] 0.9810182203 0.02857430 0.0003296316
 [29,] 0.9813048927 0.02841522 0.0003266180
 [30,] 0.9765283835 0.03372650 0.0003786375
 [31,] 0.9755295537 0.03542026 0.0003890968
 [32,] 0.9797456278 0.02993926 0.0003433763
 [33,] 0.9826722225 0.02635297 0.0003106910
 [34,] 0.9829699860 0.02618577 0.0003071976
 [35,] 0.9778337183 0.03270802 0.0003649238
 [36,] 0.9815913024 0.02814959 0.0003238255
 [37,] 0.9823601432 0.02749167 0.0003147115
 [38,] 0.9819360352 0.02731480 0.0003195789
 [39,] 0.9786955208 0.03097082 0.0003565584
 [40,] 0.9804219227 0.02928985 0.0003363697
 [41,] 0.9815872926 0.02744146 0.0003232642
 [42,] 0.9628386108 0.05285358 0.0005142561
 [43,] 0.9800406149 0.02901674 0.0003415522
 [44,] 0.9764205122 0.03205966 0.0003781221
 [45,] 0.9767269375 0.03197840 0.0003746420
 [46,] 0.9772147005 0.03315420 0.0003716132
 [47,] 0.9813288152 0.02759712 0.0003257555
 [48,] 0.9793618536 0.03012536 0.0003486376
 [49,] 0.9817893396 0.02755674 0.0003207984
 [50,] 0.9806217681 0.02908929 0.0003343813
 [51,] 0.0316056949 0.95389264 0.0395366972
 [52,] 0.0296028070 0.94872977 0.0454024594
 [53,] 0.0286173876 0.94783749 0.0476321630
 [54,] 0.0223872809 0.92770720 0.0692180759
 [55,] 0.0270812930 0.94370603 0.0525913942
 [56,] 0.0176293334 0.90641258 0.0909733970
 [57,] 0.0250470166 0.93720274 0.0588342840
 [58,] 0.0366223234 0.94996480 0.0369496088
 [59,] 0.0306699294 0.95207097 0.0426848436
 [60,] 0.0225428821 0.92585390 0.0692338080
 [61,] 0.0308000148 0.94885346 0.0457601666
 [62,] 0.0283690777 0.94481148 0.0496964174
 [63,] 0.0330679406 0.95587519 0.0390834764
 [64,] 0.0198140149 0.91826525 0.0791474467
 [65,] 0.0358022285 0.95021642 0.0363685635
 [66,] 0.0322057469 0.95393921 0.0388215073
 [67,] 0.0097008506 0.81955615 0.1781324940
 [68,] 0.0328721776 0.95386470 0.0394212192
 [69,] 0.0094660032 0.80653371 0.1917022667
 [70,] 0.0319714282 0.95200354 0.0417996562
 [71,] 0.0017828509 0.34054970 0.6578947886
 [72,] 0.0328218436 0.95328349 0.0390319075
 [73,] 0.0030642159 0.50592182 0.4920845514
 [74,] 0.0247984225 0.93766137 0.0592366407
 [75,] 0.0319809338 0.95348253 0.0399522551
 [76,] 0.0315709477 0.95306517 0.0404092252
 [77,] 0.0287184630 0.94824396 0.0477375121
 [78,] 0.0151892672 0.88779476 0.1102621661
 [79,] 0.0214098601 0.92441866 0.0725497780
 [80,] 0.0394103595 0.95386628 0.0321336184
 [81,] 0.0319875079 0.95176575 0.0420628882
 [82,] 0.0341739560 0.95410783 0.0381230046
 [83,] 0.0329120091 0.95274409 0.0395527855
 [84,] 0.0004738201 0.08444952 0.9155397426
 [85,] 0.0038946867 0.59301715 0.4045175910
 [86,] 0.0259085555 0.93851734 0.0565295528
 [87,] 0.0292193644 0.94884274 0.0461287792
 [88,] 0.0274709008 0.94503492 0.0519156698
 [89,] 0.0298283683 0.94684128 0.0464607127
 [90,] 0.0259378380 0.93893651 0.0570245660
 [91,] 0.0145677325 0.88475786 0.1129082886
 [92,] 0.0250904508 0.93772453 0.0586447219
 [93,] 0.0315055897 0.95164111 0.0423299396
 [94,] 0.0363163223 0.95139377 0.0368804866
 [95,] 0.0249925328 0.93654846 0.0595738252
 [96,] 0.0305223194 0.94895140 0.0444719017
 [97,] 0.0286145467 0.94546413 0.0492009271
 [98,] 0.0310609313 0.95160017 0.0423345277
 [99,] 0.0463381264 0.94437238 0.0294105158
[100,] 0.0294420870 0.94718436 0.0472124352
[101,] 0.0003414234 0.05331731 0.9475046082
[102,] 0.0003593058 0.05960509 0.9411971688
[103,] 0.0003641739 0.06093277 0.9394383554
[104,] 0.0003624136 0.06058208 0.9400779321
[105,] 0.0003456987 0.05666566 0.9441129008
[106,] 0.0003477834 0.05747084 0.9432660776
[107,] 0.0003657283 0.06008680 0.9408385681
[108,] 0.0003640496 0.06108034 0.9395084063
[109,] 0.0003582158 0.05966346 0.9413944937
[110,] 0.0003472991 0.05732610 0.9429418866
[111,] 0.0012373187 0.23647303 0.7621853789
[112,] 0.0003867054 0.06554060 0.9348501583
[113,] 0.0004003315 0.06816778 0.9318273151
[114,] 0.0003533344 0.05778815 0.9432811329
[115,] 0.0003455720 0.05517019 0.9457275974
[116,] 0.0003641156 0.06067100 0.9395263950
[117,] 0.0004276931 0.07449716 0.9254541599
[118,] 0.0003561426 0.05935628 0.9407345952
[119,] 0.0003423278 0.05513124 0.9458776041
[120,] 0.0004327693 0.07540231 0.9252814025
[121,] 0.0003596784 0.05988644 0.9403781356
[122,] 0.0003590647 0.05940172 0.9412444901
[123,] 0.0003487243 0.05766203 0.9432409462
[124,] 0.0010220255 0.19395389 0.8045472868
[125,] 0.0003718433 0.06250377 0.9376308959
[126,] 0.0005123433 0.09341780 0.9059852201
[127,] 0.0017056470 0.31725581 0.6808922783
[128,] 0.0011543479 0.22442202 0.7740958217
[129,] 0.0003495248 0.05756355 0.9432845074
[130,] 0.0017739760 0.34779798 0.6500801599
[131,] 0.0003799749 0.06434402 0.9359974588
[132,] 0.0014859494 0.29887470 0.7000223066
[133,] 0.0003471197 0.05687387 0.9439909237
[134,] 0.0023591536 0.43350292 0.5648769569
[135,] 0.0003750901 0.06347650 0.9375201585
[136,] 0.0003687578 0.06177769 0.9384081148
[137,] 0.0003443366 0.05644841 0.9440458018
[138,] 0.0004187278 0.07270230 0.9272646055
[139,] 0.0013758723 0.26562203 0.7327413163
[140,] 0.0005940777 0.10719845 0.8919639332
[141,] 0.0003488591 0.05756757 0.9429329095
[142,] 0.0009709762 0.17594540 0.8226786411
[143,] 0.0003593058 0.05960509 0.9411971688
[144,] 0.0003465548 0.05709878 0.9434662380
[145,] 0.0003450680 0.05672946 0.9437380453
[146,] 0.0004181651 0.07119977 0.9286111380
[147,] 0.0004301754 0.07413177 0.9260253409
[148,] 0.0005217610 0.09292737 0.9065225251
[149,] 0.0003519327 0.05815404 0.9421584824
[150,] 0.0004145777 0.07150382 0.9285225538

darch documentation built on May 29, 2017, 8:14 p.m.

Related to predict.DArch in darch...