predict
The model prediction results will be correct only if the numeric and categorical features parameters contain all the features used in the model in the same order.
- Batch of objects, matrix of numerical features, matrix of hashes of categorical features, new object with model predictions
- Batch of objects, matrix of numerical features, matrix of hashes of categorical features, specified object with model predictions
- Batch of objects, matrix of numerical features, matrix of categorical features, new object with model predictions
- Batch of objects, matrix of numerical features, matrix of categorical features, specified object with model predictions
- Object, array of numerical features, array of hashes of categorical features, new object with model predictions
- Object, array of numerical features, array of hashes of categorical features, specified object with model predictions
- Object, array of numerical features, array of categorical features, new object with model predictions
- Object, array of numerical features, array of categorical features, specified object with model predictions
Batch of objects, matrix of numerical features, matrix of hashes of categorical features, new object with model predictions
public CatBoostPredictions predict(float[][] numericFeatures,
int[][] catFeatureHashes)- Modifier and type
- Purpose
-
Apply the model to a batch of objects. Uses a matrix of numerical features and a matrix of hashes of categorical features.
- Parameters
-
Parameter Description numericFeatures A matrix of input numerical features.
catFeatureHashes A matrix of hashes of input categorical features. These hashes must be computed by the
hashCategoricalFeature(String)function.Parameter Description numericFeatures A matrix of input numerical features.
catFeatureHashes A matrix of hashes of input categorical features. These hashes must be computed by the
hashCategoricalFeature(String)function. - Returns
-
CatBoostPredictionswith predictions for a batch of objects. - Throws
-
CatBoostError— In case of errors in the native library.
Batch of objects, matrix of numerical features, matrix of hashes of categorical features, specified object with model predictions
public void predict(float[][] numericFeatures,
int[][] catFeatureHashes,
CatBoostPredictions prediction)- Modifier and type
- void
- Purpose
-
Apply the model to a batch of objects. Uses a matrix of numerical features and a matrix of hashes of categorical features.
- Parameters
-
Parameter Description numericFeatures A matrix of input numerical features.
catFeatureHashes A matrix of hashes of input categorical features. These hashes must be computed by the
hashCategoricalFeature(String)function.prediction The model's predictions.
Parameter Description numericFeatures A matrix of input numerical features.
catFeatureHashes A matrix of hashes of input categorical features. These hashes must be computed by the
hashCategoricalFeature(String)function.prediction The model's predictions.
- Returns
-
CatBoostPredictionswith predictions for a batch of objects. - Throws
-
CatBoostError— In case of errors in the native library.
Batch of objects, matrix of numerical features, matrix of categorical features, new object with model predictions
public CatBoostPredictions predict(float[][] numericFeatures,
String[][] catFeatures)- Modifier and type
- Purpose
-
Apply the model to a batch of objects. Uses a matrix of numerical features and a matrix of categorical features.
- Parameters
-
Parameter Description numericFeatures An array of input numerical features.
catFeatures A matrix of input categorical features. Parameter Description numericFeatures An array of input numerical features.
catFeatures A matrix of input categorical features. - Returns
-
CatBoostPredictionswith predictions for a batch of objects. - Throws
-
CatBoostError— In case of errors in the native library.
Batch of objects, matrix of numerical features, matrix of categorical features, specified object with model predictions
public void predict(float[][] numericFeatures,
String[][] catFeatures,
CatBoostPredictions prediction)- Modifier and type
- void
- Purpose
-
Apply the model to a batch of objects. Uses a matrix of numerical features.
- Parameters
-
Parameter Description numericFeatures A matrix of input numerical features.
catFeatures A matrix of input categorical features. prediction The model's predictions.
Parameter Description numericFeatures A matrix of input numerical features.
catFeatures A matrix of input categorical features. prediction The model's predictions.
- Returns
-
CatBoostPredictionswith predictions for a batch of objects. - Throws
-
CatBoostError— In case of errors in the native library.
Object, array of numerical features, array of hashes of categorical features, new object with model predictions
public CatBoostPredictions predict(float[] numericFeatures,
int[] catFeatureHashes)- Modifier and type
- Purpose
-
Apply the model to an object defined by features. Uses an array of numerical features and an array of hashes of categorical features.
- Parameters
-
Parameter Description numericFeatures An array of input numerical features.
catFeatureHashes An array of hashes of input categorical features. These hashes must be computed by the
hashCategoricalFeature(String)function.Parameter Description numericFeatures An array of input numerical features.
catFeatureHashes An array of hashes of input categorical features. These hashes must be computed by the
hashCategoricalFeature(String)function. - Returns
-
CatBoostPredictionswith the prediction for the specified object. - Throws
-
CatBoostError— In case of errors in the native library.
Object, array of numerical features, array of hashes of categorical features, specified object with model predictions
public void predict(float[] numericFeatures,
int[] catFeatureHashes,
CatBoostPredictions prediction)- Modifier and type
- void
- Purpose
-
Apply the model to an object defined by features. Uses an array of hashes of categorical features computed by the hashCategoricalFeature(String) function.
- Parameters
-
numericFeatures An array of input numerical features.
catFeatureHashes An array of hashes of input categorical features. These hashes must be computed by the
hashCategoricalFeature(String)function.prediction The model's predictions.
numericFeatures An array of input numerical features.
catFeatureHashes An array of hashes of input categorical features. These hashes must be computed by the
hashCategoricalFeature(String)function.prediction The model's predictions.
- Returns
-
CatBoostPredictionswith the prediction for the specified object. - Throws
-
CatBoostError— In case of errors in the native library.
Object, array of numerical features, array of categorical features, new object with model predictions
predict(float[] numericFeatures,
String[] catFeatures)- Modifier and type
- Purpose
-
Apply the model to an object defined by features.
- Parameters
-
Parameter Description numericFeatures An array of input numerical features.
catFeatures An array of input categorical features. Parameter Description numericFeatures An array of input numerical features.
catFeatures An array of input categorical features. - Returns
-
CatBoostPredictionswith the prediction for the specified object. - Throws
-
CatBoostError— In case of errors in the native library.
Object, array of numerical features, array of categorical features, specified object with model predictions
predict(float[] numericFeatures,
String[] catFeatures,
CatBoostPredictions prediction)- Modifier and type
- void
- Purpose
-
Apply the model to an object defined by features.
- Parameters
-
Parameter Description numericFeatures An array of input numerical features.
catFeatures An array of input categorical features. prediction The model's predictions.
Parameter Description numericFeatures An array of input numerical features.
catFeatures An array of input categorical features. prediction The model's predictions.
- Returns
-
CatBoostPredictionswith the prediction for the specified object. - Throws
-
CatBoostError— In case of errors in the native library.