CP_model                BaTFLED model object for 3-D response tensor
                        with CP decomposition.
Tucker_model            Factorization object for 3D Tucker models.
diagonal                Version of diag that has more consistent
                        behavior
exp_var                 Get the explained variance for a set of
                        predictions
get_data_params         Get parameters for building a model with known
                        relationships
get_influence           Given a 'model' object, rank the input
                        predictors (and combinations thereof) by thier
                        influence on the output
get_model_params        Get parameters to build a BaTFLED model
im_2_mat                Plot heatmaps of two matrices in red and blue
im_mat                  Plot a heatmap of a matrix in red and blue
input_data              Object storing input data for BaTFLED algorithm
                        with 3-D response tensor.
kernelize               Transform a matrix of input data into a matrix
                        of kernel simmilarities values
lower_bnd_CP            Calculate the lower bound of the log likelihood
                        for a trained CP model
lower_bnd_Tucker        Calculate the lower bound of the log likelihood
                        for a trained Tucker model
mk_model                Make a new model object
mk_toy                  Make a toy dataset to test the 3d BaTFLED
                        model.
mult_3d                 Multiply three matrices (or vectors) through a
                        given core tensor to form a three dimensional
                        tensor.
nrmse                   Computes the normalized root mean squared error
plot_preds              Make a scatterplot of observed vs. predicted
                        values
plot_roc                Plot reciever operating characteristic (ROC)
                        curves for two projection (A) matrices
plot_test_RMSE          Plot RMSE results from test data
plot_test_cor           Plot correlation results from test data
plot_test_exp_var       Plot explained variance results from test data
rmse                    Updates the root mean squared error for
                        training data.  Predicting both from data and
                        from just the latent (H) matrices.
rot                     Rotate a matrix for printing
safe_log                Take logarithm avoiding underflow
safe_prod               Takes the product of two matrices adding a
                        column of constants if necessary to the first
                        matrix.
show_mat                Plot matrices from a model object with im_mat
test                    Get test predictions for a 3D BaTFLED model.
test_CP                 Perform 'cold start' prediction using BaTFLED
                        algorthm for CP models
test_Tucker             Perform 'cold start' prediction for Tucker
                        models
test_results            Get RMSE & explained variance for warm and cold
                        test results
train                   Train model using BaTFLED algorthm
train_CP                Train a CP model.
train_Tucker            Train a Tucker model using BaTFLED algorthm
update_core_Tucker      Update values in the core tensor for a Tucker
                        model.
update_mode1_CP         Update the first mode in a CP model.
update_mode1_Tucker     Update the first mode in a Tucker model.
update_mode2_CP         Update the second mode in a CP model.
update_mode2_Tucker     Update the second mode in a Tucker model.
update_mode3_CP         Update the third mode in a CP model.
update_mode3_Tucker     Update the third mode in a Tucker model.
