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"feature_file_name": "multi_features_data_simu5.pkl",
"Is_train_autoencoder": false,
"autoencoder_structure": 4,
"L1": {
"noise_threshold": 0.01,
"_noise_threshold_dsp": "the number less of cluster than the threshold, consider to be noise",
"choose_model_power": "Mix",
"_choose_model_power_dsp": "options: Mix, DBSCAN",
"choose_model_vib": "Hierarchical",
"_choose_model_vib_dsp": "options, Hierarchical, DBSCAN",
"DBSCAN_power_params": [
1.2,
50,
0.9
],
"DBSCAN_params_dsp": "p1= eps, p2= min count in cluster, p3= standby threshold",
"Hierarchical_power_params": [
0.2,
1,
2,
0.2
],
"_param1_dsp": "param 1 is factor ,the stable indicattor (less than value)(difference from the reverse previous 2 level)",
"_param2_dsp": "param 2 is min number of cluster",
"_param3_dsp": "param 3 is max number of cluster",
"_param4_dsp": "param 4 is standby threshold (percentage)",
"Is_save_model": true,
"Hierarchical_vib_params": [
0.2,
4,
10,
0.5
],
"_Hierarchical_vib_params_dsp": "For vibration, the format is same",
"L1_models_name": "L1_models.pkl"
},
"L2": {
"strategy": "consensus",
"_strategy_dsp": "options: consensus, feature_fusion, meta_clustering, multi_view_cluster",
"Is_save_model": true,
"consensus_model": "GMM",
"_consensus_model_dsp": "model using on each type of sensor clusting: KMeans, GMM",
"result_type": "prob",
"_result_type_dsp": "The input the consensus matrix is each submodel result: prob (probability), one-hot",
"feature_fusion_pca_factor": 0.95,
"_feature_fusion_pca_factor_dsp": "how much the PCA catch of the variance\uff0cfor feature_fusion, meta_clustering, multi_view_cluster",
"feature_fusion_model": "GMM",
"meta_clustering_model": "GMM",
"number_class": 0,
"_number_class_dsp": "The spicify cluster number of each type of sensor. 0 mean search optimal number base on certain score",
"min_class": 3,
"_min_class_dsp": "minimum cluster number for search optimal option",
"max_class": 7,
"_max_class_dsp": "maximum cluster number (not include) for search optimal option",
"stable_indicator": 0.3,
"_stable_indicator_dsp": "when change less than the value, consider it's stable",
"covariance_type": "diag",
"_covariance_type_dsp": "GMM parameter, effect on model size"
}
} |