ML_project_template/scripts/train_config.py at main · xiaoye-hua/ML_project_template · GitHub

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# -*- coding: utf-8 -*-
# @File    : train_config.py
# @Author  : Hua Guo
# @Disc    :
from src.Pipeline.XGBRegressionPipeline import XGBRegressionPipeline
from src.FeatureCreator.FeatureCreator import FeatureCreator
from src.Pipeline.DeepFMPipeline import DeepFMPipeline
from src.Pipeline.XGBClassifierPipeline import XGBClassifierPipeline
from src.Pipeline.XGBRegClaPipeline import XGBRegClaPipeline
from src.Pipeline.XGBoostLR import XGBoostLR
from src.Pipeline.RidgeReg import RidgeReg
from src.config import breast_cancel_traget

from src.config import california_target

debug = False
dir_mark = "iris_cla"
# dir_mark = 'california_deepfm_reg'

if debug:
    raw_data_path = 'data/debug'
    model_dir = 'model_training/debug'
else:
    raw_data_path = 'data/raw_data'
    model_dir = 'model_training/'


train_config_detail = {
    "v1_0501_xgb_clareg": {
        'cla_dir': 'v1_0501_xgb_cla'
        , 'reg_dir': 'v1_0501_xgb_reg'
        , 'pipeline_class': XGBRegClaPipeline
        , 'feature_creator': FeatureCreator
        , 'train_valid': True
        , 'sparse_features': [
        ]
        , 'dense_features': [
        ]
        # , 'feature_clean_func': clean_map_feature
        , 'target_col': breast_cancel_traget
        # , 'data_dir_mark': 'v1_0501_clareg'
    },
    "california_housing_reg": {
        "pipeline_class": XGBRegressionPipeline
        , 'feature_creator': FeatureCreator
        , 'train_valid': True
        , 'sparse_features': []
        , 'dense_features': [
            'MedInc', 'HouseAge', 'AveRooms', 'AveBedrms', 'Population', 'AveOccup',
                   'Latitude', 'Longitude'
        ]
        # , 'feature_clean_func': clean_feature
        , 'target_col': california_target
    },
    "iris_cla": {
        "pipeline_class": XGBClassifierPipeline
        , 'feature_creator': FeatureCreator
        , 'train_valid': True
        , 'sparse_features': [
            'binary_feature',
            'cate_feature'
        ]
        , 'dense_features':
            [
            'zero_0', 'zero_1',
                'mean_radius', 'mean_texture', 'mean_perimeter', 'mean_area',
       'mean_smoothness', 'mean_compactness', 'mean_concavity',
       'mean_concave_points', 'mean_symmetry', 'mean_fractal_dimension',
       'radius_error', 'texture_error', 'perimeter_error', 'area_error',
       'smoothness_error', 'compactness_error', 'concavity_error',
       'concave_points_error', 'symmetry_error', 'fractal_dimension_error',
       'worst_radius', 'worst_texture', 'worst_perimeter', 'worst_area',
       'worst_smoothness', 'worst_compactness', 'worst_concavity',
       'worst_concave_points', 'worst_symmetry', 'worst_fractal_dimension']
        , 'onehot': [
            'binary_feature',
            'cate_feature'
        ]
        # , 'feature_clean_func': clean_feature
        , 'target_col': breast_cancel_traget
    },
    "iris_deepfm_cla": {
        "pipeline_class": DeepFMPipeline
        , 'task': 'binary'
        , 'feature_creator': FeatureCreator
        , 'epochs': 2
        , 'batch_size': 20
        , 'dense_to_sparse': True
        , 'train_valid': True
        , 'sparse_features': []
        , 'dense_features': ['mean_radius', 'mean_texture', 'mean_perimeter', 'mean_area',
       'mean_smoothness', 'mean_compactness', 'mean_concavity',
       'mean_concave_points', 'mean_symmetry', 'mean_fractal_dimension',
       'radius_error', 'texture_error', 'perimeter_error', 'area_error',
       'smoothness_error', 'compactness_error', 'concavity_error',
       'concave_points_error', 'symmetry_error', 'fractal_dimension_error',
       'worst_radius', 'worst_texture', 'worst_perimeter', 'worst_area',
       'worst_smoothness', 'worst_compactness', 'worst_concavity',
       'worst_concave_points', 'worst_symmetry', 'worst_fractal_dimension']
        # , 'feature_clean_func': clean_feature
        , 'target_col': breast_cancel_traget
    },
    "california_deepfm_reg": {
        "pipeline_class": DeepFMPipeline
        , 'task': 'regression'
        , 'feature_creator': FeatureCreator
        , 'epochs': 2
        , 'batch_size': 20
        , 'dense_to_sparse': True
        , 'train_valid': True
        , 'sparse_features': []
        , 'dense_features': [
            'MedInc', 'HouseAge', 'AveRooms', 'AveBedrms', 'Population', 'AveOccup',
            'Latitude', 'Longitude'
        ]
        # , 'feature_clean_func': clean_feature
        , 'target_col': california_target
    },

}