synth_multimodal | R Documentation |
Create "Multimodal" Synthetic Data using squares and arctangents
synth_multimodal(
n_cases = 10000,
init_fn = "runifmat",
init_fn_params = list(min = -10, max = 10),
n_groups = 4,
n_feat_per_group = round(seq(10, 300, length.out = n_groups)),
contrib_p = 0.33,
linear_p = 0.66,
square_p = 0.1,
atan_p = 0.1,
pair_multiply_p = 0.05,
pair_square_p = 0.05,
pair_atan_p = 0.05,
verbosity = 1L,
seed = NULL,
filename = NULL
)
n_cases |
Integer: Number of cases to create. |
init_fn |
Character: "runifmat" or "rnormmat". Use the respective functions to generate features as random uniform and random normal variables, respectively. |
init_fn_params |
Named list with arguments "min", "max" for "runifmat" and "mean", "sd" for "rnormmat". |
n_groups |
Integer: Number of feature groups / modalities to create. |
n_feat_per_group |
Integer, vector, length |
contrib_p |
Float (0, 1]: Ratio of features contributing to outcome per group. a third of the features in each group will be used to produce the outcome y |
linear_p |
Float [0, 1]: Ratio of contributing features to be included linearly. features in each group will be included |
square_p |
Float [0, 1]: Ratio of contributing features to be squared. in each group will be squared |
atan_p |
Float [0, 1]: Ratio of contributing features whose |
pair_multiply_p |
Float [0, 1] Ratio of features will be divided into pairs and multiplied. |
pair_square_p |
Float [0, 1] Ratio of features which will be divided into pairs, multiplied and squared. |
pair_atan_p |
Float [0, 1] Ratio of features which will be divided into pairs, multiplied and transformed using
|
verbosity |
Integer: Verbosity level. |
seed |
Integer: If set, pass to |
filename |
Character: Path to file to save output. |
There are no checks yet for compatibility among inputs and certain combinations may not work.
List with elements x, y, index_square, index_atan, index_pair_square
EDG
## Not run:
xmm <- synth_multimodal(
n_cases = 10000,
init_fn = "runifmat",
init_fn_params = list(min = -10, max = 10),
n_groups = 5,
n_feat_per_group = c(20, 50, 100, 200, 300),
contrib_p = .33,
linear_p = .66,
square_p = .1,
atan_p = .1,
pair_multiply_p = .1,
pair_square_p = .1,
pair_atan_p = .1,
seed = 2019
)
## End(Not run)
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