--- metadata: - name: generator content: Diplodoc Platform v5.50.3 alternate: - https://catboost.ai/docs/en/concepts/java-reference_catboostmodel__predict.md --- > **Documentation Index:** Fetch the complete configuration index at https://catboost.ai/docs/en/llms.txt # predict The CatBoost Java package provides several methods for applying a model to different types of objects and input features. {% note info %} 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. {% endnote %} ## Batch of objects, matrix of numerical features, matrix of hashes of categorical features, new object with model predictions {#batch-of-object-matrix-of-numerical-features-matrix-of-hashes-of-catfeatures-new-object} ```java public CatBoostPredictions predict(float[][] numericFeatures, int[][] catFeatureHashes) ``` #### Modifier and type [CatBoostPredictions](https://catboost.ai/docs/en/concepts/java-reference_catboostpredictions.md) #### 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 {#batch-of-object-matrix-of-numerical-features-matrix-of-hashes-of-catfeatures-object-from-the-constructor} ```java 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 {#batch-of-objects-matrixnumfeatures-matrixcatfeatures-newobject} ```java public CatBoostPredictions predict(float[][] numericFeatures, String[][] catFeatures) ``` #### Modifier and type [CatBoostPredictions](https://catboost.ai/docs/en/concepts/java-reference_catboostpredictions.md) #### 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 {#batch-of-objects-matrixnumfeatures-matrixcatfeatures-objectfromconstructor} ```java 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 {#object-numfeaturesarray-catfeatureshashesarray-newobject} ```java public CatBoostPredictions predict(float[] numericFeatures, int[] catFeatureHashes) ``` #### Modifier and type [CatBoostPredictions](https://catboost.ai/docs/en/concepts/java-reference_catboostpredictions.md) #### 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 {#object-numfeaturesarray-catfeatureshashesarray-objectfromconstructor} ```java 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 {#object-numfeaturesarray-catfeaturesarray-newobject} ```java predict(float[] numericFeatures, String[] catFeatures) ``` #### Modifier and type [CatBoostPredictions](https://catboost.ai/docs/en/concepts/java-reference_catboostpredictions.md) #### 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 {#object-numfeaturesarray-catfeaturesarray-objectfromconstructor} ```java 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.