org.nd4j.linalg.lossfunctions.LossFunctions Maven / Gradle / Ivy
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* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://www.apache.org/licenses/LICENSE-2.0.
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* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* under the License.
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* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.nd4j.linalg.lossfunctions;
import org.nd4j.linalg.lossfunctions.impl.*;
/**
* Central class for loss functions
* @author Adam Gibson
*/
public class LossFunctions {
/**
* MSE: Mean Squared Error: Linear Regression
* EXPLL: Exponential log likelihood: Poisson Regression
* XENT: Cross Entropy: Binary Classification
* MCXENT: Multiclass Cross Entropy
* RMSE_XENT: RMSE Cross Entropy
* SQUARED_LOSS: Squared Loss
* NEGATIVELOGLIKELIHOOD: Negative Log Likelihood
*/
public enum LossFunction {
MSE, L1, @Deprecated EXPLL, XENT, MCXENT, @Deprecated RMSE_XENT, SQUARED_LOSS, RECONSTRUCTION_CROSSENTROPY, NEGATIVELOGLIKELIHOOD, @Deprecated CUSTOM, COSINE_PROXIMITY, HINGE, SQUARED_HINGE, KL_DIVERGENCE, MEAN_ABSOLUTE_ERROR, L2, MEAN_ABSOLUTE_PERCENTAGE_ERROR, MEAN_SQUARED_LOGARITHMIC_ERROR, POISSON;
public ILossFunction getILossFunction() {
switch (this) {
case MSE:
case SQUARED_LOSS:
return new LossMSE();
case L1:
return new LossL1();
case XENT:
return new LossBinaryXENT();
case MCXENT:
return new LossMCXENT();
case KL_DIVERGENCE:
case RECONSTRUCTION_CROSSENTROPY:
return new LossKLD();
case NEGATIVELOGLIKELIHOOD:
return new LossNegativeLogLikelihood();
case COSINE_PROXIMITY:
return new LossCosineProximity();
case HINGE:
return new LossHinge();
case SQUARED_HINGE:
return new LossSquaredHinge();
case MEAN_ABSOLUTE_ERROR:
return new LossMAE();
case L2:
return new LossL2();
case MEAN_ABSOLUTE_PERCENTAGE_ERROR:
return new LossMAPE();
case MEAN_SQUARED_LOGARITHMIC_ERROR:
return new LossMSLE();
case POISSON:
case EXPLL:
return new LossPoisson();
default:
//Custom, RMSE_XENT
throw new UnsupportedOperationException("Unknown or not supported loss function: " + this);
}
}
}
}