apply_gradient | Compute gradient contribution for exact response |
apply_gradient2 | Compute gradient contribution for exact response |
coef.k_ontram | S3 methods for 'k_ontram' |
coef.ontram | Function for coef for simple ontram |
compute_kappa | compute Cohen's weighted kappa |
compute_logLik | Compute logLik contributions for exact response |
compute_logLik2 | Compute logLik contributions for exact response |
dot-initializer_bias_gamma | initializer for equal class probs |
dot-to_gamma | theta to gamma |
dot-to_theta | gamma to theta |
eval_batchwise | Evaluate fitted ontram models |
expected_score | Expected weighted kappa score |
fit_k_ontram | Function for estimating a 'k_ontram' or 'k_ontram_ci' model |
fit_k_ontram_augmented_data | Function for estimating a 'k_ontram' or 'k_ontram_ci' model... |
fit_ontram | Function for estimating the model |
fit_ontram2 | Function for estimating the model |
fit_ontram3 | Function for estimating the model |
gamma_to_theta | Transform raw intercept function to constrained one |
get_expected | expected number of agreements under independence |
get_loss | get kappa loss python function |
get_metric | get kappa metric python function |
get_weights_by_name | Get weights by name of layer |
kappa_loss | Weighted kappa loss function (R) |
k_mod_baseline | Baseline model |
k_ontram | Keras interface to ONTRAMs |
k_ontram_acc | Accuracy function |
k_ontram_auc | AUC function |
k_ontram_binll | Binary logLik function |
k_ontram_cqwk | Continuous qwk |
k_ontram_loss | Another keras implementation of the ontram loss |
k_ontram_qwk | Discrete qwk |
k_ontram_rps | RPS loss |
layer_trafo_intercept | Layer for transforming raw intercepts using softplus function |
load_model_ontram | Load ontram model |
load_ontram_history | Save ontram history |
metric_acc | Accuracy metric |
metric_binll | Binary NLL metric |
metric_cqwk | Continuous qwk metric |
metric_k_auc | Accuracy metric |
metric_nll | NLL metric |
metric_qwk | Discrete qwk metric |
metric_rps | CRPS metric |
mod_baseline | Sequential model for the intercept function |
mod_shift | Sequential model for the shift function |
mod_weights.ontram | Extract model weights |
ontram | General ordinal transformation neural network |
ontram_polr | Combine intercept and tabular model |
pgompertz | Gompertz cdf python function |
pgumbel | Gumbel cdf python function |
plot.ontram_history | Plot ontram history |
predict.k_ontram | S3 methods for 'k_ontram' |
predict.ontram | Function for predicting cdf, pdf and class and compute logLik |
predict.ontram_rv | Function for predicting cdf, pdf and class and compute logLik |
rps | RPS with weights |
save_k_hist | Save history of keras model |
save_model_ontram | Save ontram model |
save_ontram_history | Save ontram history |
simulate.k_ontram | Simulate Responses |
simulate.ontram | Simulate Responses |
warmstart.k_ontram | Set initial weights |
warmstart.k_ontram_ci | Set initial weights |
warmstart.ontram | Set initial weights |
warmstart.ontram_rv | Set initial weights |
weight_scheme | Weighting scheme for Cohen's kappa |
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