Description Usage Arguments Value Examples
Get RMSE & explained variance for warm and cold test results
1 2 3 4 |
m |
a |
d |
an input data object created with |
test.results |
an object generated by this function that will combined with the new results |
verbose |
Logical indicating whether to print the resulting prediction measures (TRUE) |
warm.resp |
True responses for warm test data (optional). |
test.m1 |
True responses for mode 1 cold test data (optional). |
test.m2 |
True responses for mode 2 cold test data (optional). |
test.m3 |
True responses for mode 3 cold test data (optional). |
test.m1m2 |
True responses for mode 1/2 combination cold test data (optional). |
test.m1m3 |
True responses for mode 1/3 combination cold test data (optional). |
test.m2m3 |
True responses for mode 2/3 combination cold test data (optional). |
test.m1m2m3 |
True responses for mode 1/2/3 combination cold test data (optional). |
list of results TODO: add more here
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | data.params <- get_data_params(c('decomp=Tucker'))
toy <- mk_toy(data.params)
# Make training data object excluding the first two samples for modes 1 & 2.
train.data <- input_data$new(mode1.X=toy$mode1.X[-(1:2),-1],
mode2.X=toy$mode2.X[-(1:2),-1],
mode3.X=toy$mode3.X[,-1],
resp=toy$resp)
# Remove some responses for warm prediction
warm.ind <- sample(1:prod(dim(train.data$resp)), 20)
warm.resp <- train.data$resp[warm.ind]
train.data$resp[warm.ind] <- NA
# Make testing objects
m1.test.data <- input_data$new(mode1.X=toy$mode1.X[1:2,-1],
mode2.X=toy$mode2.X[-(1:2),-1],
mode3.X=toy$mode3.X[,-1],
resp=toy$resp[1:2,-(1:2),])
m2.test.data <- input_data$new(mode1.X=toy$mode1.X[-(1:2),-1],
mode2.X=toy$mode2.X[1:2,-1],
mode3.X=toy$mode3.X[,-1],
resp=toy$resp[-(1:2),1:2,])
m1m2.test.data <- input_data$new(mode1.X=toy$mode1.X[1:2,-1],
mode2.X=toy$mode2.X[1:2,-1],
mode3.X=toy$mode3.X[,-1],
resp=toy$resp[1:2,1:2,])
model.params <- get_model_params(c('decomp=Tucker'))
toy.model <- mk_model(train.data, model.params)
toy.model$rand_init(model.params)
toy.model$iter <- 1
test.results <- numeric(0)
test_results(m=toy.model, d=train.data, warm.resp=warm.resp,
test.m1=m1.test.data, test.m2=m2.test.data,
test.m1m2=m1m2.test.data)
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