Package index
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autoplot(<brulee_mlp>)autoplot(<brulee_logistic_reg>)autoplot(<brulee_multinomial_reg>)autoplot(<brulee_linear_reg>)autoplot(<brulee_resnet>)autoplot(<brulee_auto_int>)autoplot(<brulee_saint>)autoplot(<brulee_rln>) - Plot model loss over epochs
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coef(<brulee_logistic_reg>)coef(<brulee_linear_reg>)coef(<brulee_mlp>)coef(<brulee_multinomial_reg>)coef(<brulee_resnet>)coef(<brulee_rln>) - Extract Model Coefficients
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brulee_activations() - Activation functions for neural networks in brulee
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brulee_auto_int() - Fit AutoInt models for tabular data
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brulee_chronos() - Chronos-2 pretrained forecasting model
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brulee_linear_reg() - Fit a linear regression model
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brulee_logistic_reg() - Fit a logistic regression model
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brulee_mlp()brulee_mlp_two_layer() - Fit neural networks
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brulee_multinomial_reg() - Fit a multinomial regression model
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brulee_resnet() - Fit residual neural networks (ResNet)
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brulee_rln() - Fit Regularization Learning Networks (RLN)
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brulee_saint() - Fit SAINT models for tabular data
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matrix_to_dataset() - Convert data to torch format
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predict(<brulee_auto_int>) - Predict from a
brulee_auto_int -
predict(<brulee_chronos>) - Predict from a
brulee_chronosmodel -
predict(<brulee_linear_reg>) - Predict from a
brulee_linear_reg -
predict(<brulee_logistic_reg>) - Predict from a
brulee_logistic_reg -
predict(<brulee_mlp>) - Predict from a
brulee_mlp -
predict(<brulee_multinomial_reg>) - Predict from a
brulee_multinomial_reg -
predict(<brulee_resnet>) - Predict from a
brulee_resnet -
predict(<brulee_rln>) - Predict from a
brulee_rln -
predict(<brulee_saint>) - Predict from a
brulee_saint -
schedule_decay_time()schedule_decay_expo()schedule_step()schedule_cyclic()set_learn_rate() - Change the learning rate over time
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summary(<brulee_mlp>)summary(<brulee_resnet>)summary(<brulee_rln>)summary(<brulee_auto_int>)summary(<brulee_saint>) - Summarize the architecture of a brulee model
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training_efficiency - Training Efficiency