predict
- 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
The CatBoost Java package provides several methods for applying a model to different types of objects and input features.
Note
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
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
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
CatBoostPredictions with 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
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
CatBoostPredictions with 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
numericFeatures
An array of input numerical features.
catFeatures
A matrix of input categorical features.
Returns
CatBoostPredictions with 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
numericFeatures
A matrix of input numerical features.
catFeatures
A matrix of input categorical features.
prediction
The model's predictions.
Returns
CatBoostPredictions with 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
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
CatBoostPredictions with 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.
Returns
CatBoostPredictions with 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
numericFeatures
An array of input numerical features.
catFeatures
An array of input categorical features.
Returns
CatBoostPredictions with 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
numericFeatures
An array of input numerical features.
catFeatures
An array of input categorical features.
prediction
The model's predictions.
Returns
CatBoostPredictions with the prediction for the specified object.
Throws
CatBoostError — In case of errors in the native library.