YModel supports presenting model performance information with charts on IDE. But, when the YModel is integrated into a third-party program or when users use the Yimming as an external library, the chart functionality is disabled. Gladly the YModel offers a special interface to get the information in JSON format. Here let’s learn about parameters for getting model performance.
Parameters
"Importance": //Importance degree
"ModelPerformanceInfo": //Model performance
"LiftAndRecallTable": // Recall lift table
"CumulativeRecall":0.0945945945945946, // Cumulative recall
"Decile":1, //Decile
"CumulativeLift":1.9654654654654653, // Cumulative lift
"Recall":0.0945945945945946, //Recall
"Lift":1.9654654654654653 //Lift
"KS":0.30674479789524034, //KS
"RocTable": //ROC curve
"1-specificity":0, //1-TNR(true negative rate )
"sensitivity":0.013513513513513514 //true positive rate(TPR)
"AccuTable": // Accuracy table
"precision":0.4010989010989011, //Precesion
"recall":0.9864864864864865, //Recall
"accuracy":0.4117647058823529, //Accuracy
"threshold":0.05000000074505806 //Threshold
"GINI":0.42107151399186793, // Gini system
"AUC":0.710535756995934 // AUC
"ModelPresentInfo": //Model description
"name":"XGBClassification_1", // Model name
"value":"0.6934943793350874", //model value
"properties": //model properties
Example
Model presentation scoring over Titanic passenger data:
{
"Importance":
{
"Embarked":0,
"Pclass":0,
"Ticket":0,
"Survived":0,
"PassengerId":0,
"Parch":0.3248725801014045,
"Cabin":0,
"Sex":0,
"SibSp":0,
"Age":0.8937610252531971,
"Fare":1
},
"ModelPerformanceInfo":
[
{
"LiftAndRecallTable":
[
{
"CumulativeRecall":0.0945945945945946,
"Decile":1,
"CumulativeLift":1.9654654654654653,
"Recall":0.0945945945945946,
"Lift":1.9654654654654653
},
{
"CumulativeRecall":0.17567567567567569,
"Decile":2,
"CumulativeLift":1.825075075075075,
"Recall":0.08108108108108109,
"Lift":1.6846846846846846
},
{
"CumulativeRecall":0.2567567567567568,
"Decile":3,
"CumulativeLift":1.7782782782782782,
"Recall":0.08108108108108109,
"Lift":1.6846846846846846
},
{
"CumulativeRecall":0.3378378378378379,
"Decile":4,
"CumulativeLift":1.75487987987988,
"Recall":0.08108108108108109,
"Lift":1.6846846846846846
},
{
"CumulativeRecall":0.4054054054054055,
"Decile":5,
"CumulativeLift":1.6846846846846848,
"Recall":0.06756756756756757,
"Lift":1.4039039039039038
},
{
"CumulativeRecall":0.4324324324324325,
"Decile":6,
"CumulativeLift":1.4974974974974975,
"Recall":0.02702702702702703,
"Lift":0.5615615615615615
},
{
"CumulativeRecall":0.48648648648648657,
"Decile":7,
"CumulativeLift":1.444015444015444,
"Recall":0.05405405405405406,
"Lift":1.123123123123123
},
{
"CumulativeRecall":0.5540540540540542,
"Decile":8,
"CumulativeLift":1.4390015015015016,
"Recall":0.06756756756756757,
"Lift":1.4039039039039038
},
{
"CumulativeRecall":0.5945945945945947,
"Decile":9,
"CumulativeLift":1.372706039372706,
"Recall":0.04054054054054054,
"Lift":0.8423423423423423
},
{
"CumulativeRecall":0.6486486486486488,
"Decile":10,
"CumulativeLift":1.3477477477477477,
"Recall":0.05405405405405406,
"Lift":1.123123123123123
},
{
"CumulativeRecall":0.6756756756756759,
"Decile":11,
"CumulativeLift":1.2762762762762763,
"Recall":0.02702702702702703,
"Lift":0.5615615615615615
},
{
"CumulativeRecall":0.7432432432432434,
"Decile":12,
"CumulativeLift":1.286911911911912,
"Recall":0.06756756756756757,
"Lift":1.4039039039039038
},
{
mulativeRecall":0.7972972972972975,
"Decile":13,
"CumulativeLift":1.2743127743127745,
"Recall":0.05405405405405406,
"Lift":1.123123123123123
},
{
"CumulativeRecall":0.8513513513513515,
"Decile":14,
"CumulativeLift":1.2635135135135136,
"Recall":0.05405405405405406,
"Lift":1.123123123123123
},
{
"CumulativeRecall":0.9054054054054056,
"Decile":15,
"CumulativeLift":1.254154154154154,
"Recall":0.05405405405405406,
"Lift":1.123123123123123
},
{
"CumulativeRecall":0.9054054054054056,
"Decile":16,
"CumulativeLift":1.1757695195195195,
"Recall":0,
"Lift":0
},
{
"CumulativeRecall":0.9189189189189191,
"Decile":17,
"CumulativeLift":1.1231231231231231,
"Recall":0.013513513513513514,
"Lift":0.2807807807807807
},
{
"CumulativeRecall":0.9729729729729731,
"Decile":18,
"CumulativeLift":1.123123123123123,
"Recall":0.05405405405405406,
"Lift":1.123123123123123
},
{
"CumulativeRecall":0.9729729729729731,
"Decile":19,
"CumulativeLift":1.0640113798008535,
"Recall":0,
"Lift":0
},
{
"CumulativeRecall":1.0000000000000002,
"Decile":20,
"CumulativeLift":1.0266047297297296,
"Recall":0.02702702702702703,
"Lift":0.31587837837837834
}
],
"KS":0.30674479789524034,
"RocTable":
[
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"1-specificity":0,
"sensitivity":0.013513513513513514
},
{
"1-specificity":0,
"sensitivity":0.02702702702702703
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"sensitivity":0.08108108108108109
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],
"AccuTable":
[
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"accuracy":0.4117647058823529,
"threshold":0.05000000074505806
},
{
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"accuracy":0.5080213903743316,
"threshold":0.10000000004139212
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},
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"threshold":0.7499999908937346
},
{
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}
],
"GINI":0.42107151399186793,
"AUC":0.710535756995934
}
],
"ModelPresentInfo":
[
{
"name":"XGBClassification_1",
"value":"0.6934943793350874",
"properties":
{
"reg_lambda":"1",
"colsample_bytree":"1",
"base_score":"0.5",
"scale_pos_weight":"1",
"n_jobs":"4",
"max_depth":"6",
"random_state":"0",
"n_estimators":"150",
"reg_alpha":"0",
"booster":"gbtree",
"objective":"binary:logistic",
"missing":null,
"subsample":"1",
"colsample_bylevel":"1",
"learning_rate":"0.1",
"max_delta_step":"0",
"min_child_weight":"1",
"gamma":"0",
"verbosity":"0"
}
},
{
"name":"RFClassification_1",
"value":"0.6901458981105",
"properties":
{
"criterion":"gini",
"oob_score":"false",
"min_samples_split":"50",
"max_depth":"6",
"n_jobs":"-1",
"n_estimators":"100",
"bootstrap":"true",
"random_state":"0",
"min_weight_fraction_leaf":"0",
"min_impurity_decrease":"1e-07",
"min_samples_leaf":"50",
"warm_start":"false",
"verbose":"0",
"max_features":null,
"max_leaf_nodes":null,
"class_weight":null
}
},
{
"name":"FNNClassification_1",
"value":"0.6566012915570437",
"properties":
{
"beta_1":"0.9",
"beta_2":"0.999",
"batch_size":"auto",
"random_state":"0",
"early_stopping":"true",
"warm_start":"false",
"hidden_layer_sizes":
[
6,
4
],
"momentum":"0.9",
"verbose":"false",
"tol":"1e-05",
"epsilon":"1e-08",
"alpha":"1e-05",
"power_t":"0.5",
"nesterovs_momentum":"true",
"validation_fraction":"0.1",
"shuffle":"true",
"activation":"tanh",
"learning_rate_init":"0.001",
"max_iter":"200",
"learning_rate":"constant",
"solver":"lbfgs"
}
},
{
"name":"RidgeClassification_1",
"value":"0.6758550585984215",
"properties":
{
"tol":"1e-05",
"fit_intercept":"true",
"alpha":"0.5",
"normalize":"false",
"class_weight":null,
"random_state":"0",
"max_iter":"200",
"copy_X":"true",
"solver":"auto"
}
},
{
"name":"TreeClassification_1",
"value":"0.6918201387227936",
"properties":
{
"max_features":null,
"criterion":"gini",
"max_leaf_nodes":null,
"min_samples_split":"50",
"presort":"false",
"max_depth":"6",
"class_weight":null,
"random_state":"0",
"min_weight_fraction_leaf":"0",
"min_impurity_decrease":"1e-08",
"splitter":"best",
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