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Merge pull request #142 from Hector-hedb12/issue-121-MLP-multi-class-…
…softmax-classifier Issue 139: MLP multi-class classifier
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mlprimitives/jsons/keras.Sequential.MLPMultiClassClassifier.json
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| { | ||
| "name": "keras.Sequential.MLPMultiClassClassifier", | ||
| "contributors": [ | ||
| "Hector Dominguez <[email protected]>" | ||
| ], | ||
| "description": "Multilayer Perceptron (MLP) for multi-class softmax classification", | ||
| "classifiers": { | ||
| "type": "estimator", | ||
| "subtype": "classifier" | ||
| }, | ||
| "modalities": [], | ||
| "primitive": "mlprimitives.adapters.keras.Sequential", | ||
| "fit": { | ||
| "method": "fit", | ||
| "args": [ | ||
| { | ||
| "name": "X", | ||
| "type": "ndarray" | ||
| }, | ||
| { | ||
| "name": "y", | ||
| "type": "array" | ||
| }, | ||
| { | ||
| "name": "classes", | ||
| "type": "int", | ||
| "description": "Number of classes" | ||
| }, | ||
| { | ||
| "name": "features", | ||
| "type": "int", | ||
| "description": "Number of features in X" | ||
| } | ||
| ] | ||
| }, | ||
| "produce": { | ||
| "method": "predict", | ||
| "args": [ | ||
| { | ||
| "name": "X", | ||
| "type": "ndarray" | ||
| } | ||
| ], | ||
| "output": [ | ||
| { | ||
| "name": "y", | ||
| "type": "array" | ||
| } | ||
| ] | ||
| }, | ||
| "hyperparameters": { | ||
| "fixed": { | ||
| "classification": { | ||
| "type": "bool", | ||
| "default": true | ||
| }, | ||
| "loss": { | ||
| "type": "str", | ||
| "default": "keras.losses.categorical_crossentropy" | ||
| }, | ||
| "optimizer": { | ||
| "type": "str", | ||
| "default": "keras.optimizers.SGD" | ||
| }, | ||
| "metrics": { | ||
| "type": "list", | ||
| "default": [ | ||
| "accuracy" | ||
| ] | ||
| }, | ||
| "epochs": { | ||
| "type": "int", | ||
| "default": 20 | ||
| }, | ||
| "layers": { | ||
| "type": "list", | ||
| "default": [ | ||
| { | ||
| "class": "keras.layers.Dense", | ||
| "parameters": { | ||
| "units": "dense_1_units", | ||
| "activation": "relu", | ||
| "input_dim": "features" | ||
| } | ||
| }, | ||
| { | ||
| "class": "keras.layers.Dropout", | ||
| "parameters": { | ||
| "rate": "dropout_1_rate" | ||
| } | ||
| }, | ||
| { | ||
| "class": "keras.layers.Dense", | ||
| "parameters": { | ||
| "units": "dense_2_units", | ||
| "activation": "relu" | ||
| } | ||
| }, | ||
| { | ||
| "class": "keras.layers.Dropout", | ||
| "parameters": { | ||
| "rate": "dropout_2_rate" | ||
| } | ||
| }, | ||
| { | ||
| "class": "keras.layers.Dense", | ||
| "parameters": { | ||
| "units": "classes", | ||
| "activation": "softmax" | ||
| } | ||
| } | ||
| ] | ||
| } | ||
| }, | ||
| "tunable": { | ||
| "dense_1_units": { | ||
| "type": "int", | ||
| "default": 64, | ||
| "range": [ | ||
| 1, | ||
| 500 | ||
| ] | ||
| }, | ||
| "dense_2_units": { | ||
| "type": "int", | ||
| "default": 64, | ||
| "range": [ | ||
| 1, | ||
| 500 | ||
| ] | ||
| }, | ||
| "dropout_1_rate": { | ||
| "type": "float", | ||
| "default": 0.5, | ||
| "range": [ | ||
| 0.0, | ||
| 0.75 | ||
| ] | ||
| }, | ||
| "dropout_2_rate": { | ||
| "type": "float", | ||
| "default": 0.5, | ||
| "range": [ | ||
| 0.0, | ||
| 0.75 | ||
| ] | ||
| }, | ||
| "batch_size": { | ||
| "type": "int", | ||
| "default": 128 | ||
| } | ||
| } | ||
| } | ||
| } |
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| { | ||
| "metadata": { | ||
| "name": "keras.Sequential.MLPMultiClassClassifier", | ||
| "data_type": "single_table", | ||
| "task_type": "classification" | ||
| }, | ||
| "validation": { | ||
| "dataset": "iris", | ||
| "context": {} | ||
| }, | ||
| "primitives": [ | ||
| "mlprimitives.custom.counters.UniqueCounter", | ||
| "mlprimitives.custom.counters.count_features", | ||
| "keras.Sequential.MLPMultiClassClassifier" | ||
| ], | ||
| "input_names": { | ||
| "mlprimitives.custom.counters.UniqueCounter#1": { | ||
| "X": "y" | ||
| } | ||
| }, | ||
| "output_names": { | ||
| "mlprimitives.custom.counters.UniqueCounter#1": { | ||
| "counts": "classes" | ||
| } | ||
| } | ||
| } |