| archive | FT::Feat | private |
| best_complexity | FT::Feat | private |
| best_ind | FT::Feat | private |
| best_med_score | FT::Feat | private |
| calculate_stats(const DataRef &d) | FT::Feat | private |
| evaluator | FT::Feat | private |
| Feat() | FT::Feat | inline |
| final_model(DataRef &d) | FT::Feat | private |
| fit(MatrixXf &X, VectorXf &y) | FT::Feat | |
| fit(MatrixXf &X, VectorXf &y, LongData &Z) | FT::Feat | |
| get_archive(bool front) | FT::Feat | |
| get_archive_size() | FT::Feat | inline |
| get_backprop() | FT::Feat | inline |
| get_batch_size() | FT::Feat | inline |
| get_classification() | FT::Feat | |
| get_coefs() | FT::Feat | |
| get_complexity() | FT::Feat | |
| get_corr_delete_mutate() | FT::Feat | inline |
| get_cross_rate() | FT::Feat | |
| get_dim() | FT::Feat | |
| get_dtypes() | FT::Feat | |
| get_eqn(bool sort=false) | FT::Feat | |
| get_erc() | FT::Feat | |
| get_fb() | FT::Feat | |
| get_feature_names() | FT::Feat | inline |
| get_functions() | FT::Feat | inline |
| get_gens() | FT::Feat | |
| get_hillclimb() | FT::Feat | inline |
| get_ind_eqn(bool sort, Individual &ind) | FT::Feat | |
| get_is_fitted() | FT::Feat | inline |
| get_iters() | FT::Feat | inline |
| get_logfile() | FT::Feat | |
| get_lr() | FT::Feat | inline |
| get_max_depth() | FT::Feat | |
| get_max_dim() | FT::Feat | |
| get_max_size() | FT::Feat | |
| get_max_stall() | FT::Feat | |
| get_max_time() | FT::Feat | inline |
| get_ml() | FT::Feat | |
| get_model(bool sort=true) | FT::Feat | |
| get_n_jobs() | FT::Feat | inline |
| get_n_nodes() | FT::Feat | |
| get_n_params() | FT::Feat | |
| get_normalize() | FT::Feat | inline |
| get_num_features() | FT::Feat | |
| get_objectives() | FT::Feat | inline |
| get_otype() | FT::Feat | inline |
| get_otypes() | FT::Feat | |
| get_pop_size() | FT::Feat | |
| get_protected_groups() | FT::Feat | inline |
| get_random_state() | FT::Feat | inline |
| get_random_state_() | FT::Feat | inline |
| get_representation() | FT::Feat | |
| get_residual_xo() | FT::Feat | inline |
| get_root_xo_rate() | FT::Feat | inline |
| get_save_pop() | FT::Feat | inline |
| get_scorer() | FT::Feat | |
| get_scorer_() | FT::Feat | |
| get_sel() | FT::Feat | inline |
| get_shuffle() | FT::Feat | |
| get_simplify() | FT::Feat | inline |
| get_softmax_norm() | FT::Feat | inline |
| get_split() | FT::Feat | |
| get_stagewise_xo() | FT::Feat | inline |
| get_stagewise_xo_tol() | FT::Feat | inline |
| get_starting_pop() | FT::Feat | inline |
| get_stats() | FT::Feat | |
| get_surv() | FT::Feat | inline |
| get_tune_final() | FT::Feat | inline |
| get_tune_initial() | FT::Feat | inline |
| get_val_from_arch() | FT::Feat | inline |
| get_verbosity() | FT::Feat | |
| get_Z(string s, int *idx, int idx_size) | FT::Feat | |
| init() | FT::Feat | |
| initial_model(DataRef &d) | FT::Feat | private |
| is_fitted | FT::Feat | |
| load(const json &j) | FT::Feat | |
| load_best_ind(string filename) | FT::Feat | |
| load_from_file(string filename) | FT::Feat | |
| load_population(string filename, bool justfront=false) | FT::Feat | |
| log_stats(std::ofstream &log) | FT::Feat | private |
| logfile | FT::Feat | private |
| min_loss | FT::Feat | private |
| min_loss_v | FT::Feat | private |
| N | FT::Feat | private |
| NLOHMANN_DEFINE_TYPE_INTRUSIVE(Feat, params, pop, selector, survivor, archive, use_arch, survival, N, min_loss, min_loss_v, best_med_score, best_complexity, str_dim, starting_pop, best_ind, is_fitted) | FT::Feat | private |
| params | FT::Feat | private |
| pop | FT::Feat | private |
| predict(MatrixXf &X, LongData &Z) | FT::Feat | |
| predict(MatrixXf &X) | FT::Feat | |
| predict_archive(int id, MatrixXf &X) | FT::Feat | |
| predict_archive(int id, MatrixXf &X, LongData &Z) | FT::Feat | |
| predict_labels(MatrixXf &X, LongData Z=LongData()) | FT::Feat | |
| predict_proba(MatrixXf &X, LongData &Z) | FT::Feat | |
| predict_proba(MatrixXf &X) | FT::Feat | |
| predict_proba_archive(int id, MatrixXf &X, LongData &Z) | FT::Feat | |
| predict_proba_archive(int id, MatrixXf &X) | FT::Feat | |
| print_stats(std::ofstream &log, float fraction) | FT::Feat | private |
| run_generation(unsigned int g, vector< size_t > survivors, DataRef &d, std::ofstream &log, float percentage, unsigned &stall_count) | FT::Feat | |
| save() const | FT::Feat | |
| save_pop | FT::Feat | private |
| save_to_file(string filename) | FT::Feat | |
| score(MatrixXf &X, const VectorXf &y, LongData Z=LongData()) | FT::Feat | |
| selector | FT::Feat | private |
| set_backprop(bool bp) | FT::Feat | |
| set_batch_size(int bs) | FT::Feat | |
| set_classification(bool classification) | FT::Feat | |
| set_corr_delete_mutate(bool s) | FT::Feat | |
| set_cross_rate(float cross_rate) | FT::Feat | |
| set_dtypes(vector< char > dtypes) | FT::Feat | |
| set_erc(bool erc) | FT::Feat | |
| set_fb(float fb) | FT::Feat | |
| set_feature_names(string s) | FT::Feat | inline |
| set_functions(const vector< string > &fns) | FT::Feat | inline |
| set_gens(int gens) | FT::Feat | |
| set_hillclimb(bool hc) | FT::Feat | |
| set_is_fitted(bool f) | FT::Feat | inline |
| set_iters(int iters) | FT::Feat | |
| set_logfile(string s) | FT::Feat | |
| set_lr(float lr) | FT::Feat | |
| set_max_depth(unsigned int max_depth) | FT::Feat | |
| set_max_dim(unsigned int max_dim) | FT::Feat | |
| set_max_stall(int max_stall) | FT::Feat | |
| set_max_time(int time) | FT::Feat | |
| set_ml(string ml) | FT::Feat | |
| set_n_jobs(unsigned t) | FT::Feat | |
| set_normalize(bool in) | FT::Feat | inline |
| set_objectives(const vector< string > &obj) | FT::Feat | inline |
| set_otype(char ot) | FT::Feat | |
| set_pop_size(int pop_size) | FT::Feat | |
| set_protected_groups(string pg) | FT::Feat | |
| set_random_state(int random_state) | FT::Feat | |
| set_residual_xo(bool res_xo=true) | FT::Feat | inline |
| set_root_xo_rate(float cross_rate) | FT::Feat | |
| set_save_pop(int pp) | FT::Feat | inline |
| set_scorer(string s) | FT::Feat | |
| set_sel(string in) | FT::Feat | inline |
| set_selection(string sel) | FT::Feat | |
| set_shuffle(bool sh) | FT::Feat | |
| set_simplify(float s) | FT::Feat | |
| set_softmax_norm(bool sftmx=true) | FT::Feat | inline |
| set_split(float sp) | FT::Feat | |
| set_stagewise_xo(bool sem_xo=true) | FT::Feat | inline |
| set_stagewise_xo_tol(int tol) | FT::Feat | inline |
| set_starting_pop(string sp) | FT::Feat | inline |
| set_surv(string in) | FT::Feat | inline |
| set_survival(string surv) | FT::Feat | |
| set_tune_final(bool in) | FT::Feat | inline |
| set_tune_initial(bool in) | FT::Feat | inline |
| set_use_batch() | FT::Feat | |
| set_val_from_arch(bool in) | FT::Feat | inline |
| set_verbosity(int verbosity) | FT::Feat | |
| simplify | FT::Feat | private |
| simplify_model(DataRef &d, Individual &) | FT::Feat | private |
| starting_pop | FT::Feat | private |
| stats | FT::Feat | private |
| str_dim | FT::Feat | private |
| survival | FT::Feat | private |
| survivor | FT::Feat | private |
| timer | FT::Feat | private |
| transform(MatrixXf &X) | FT::Feat | |
| transform(MatrixXf &X, LongData &Z) | FT::Feat | |
| transform(MatrixXf &X, LongData Z, Individual *ind) | FT::Feat | |
| univariate_initial_model(DataRef &d, int n_feats) | FT::Feat | private |
| update_best(const DataRef &d, bool val=false) | FT::Feat | private |
| update_stall_count(unsigned &stall_count, bool updated) | FT::Feat | private |
| use_arch | FT::Feat | private |
| val_from_arch | FT::Feat | private |
| variator | FT::Feat | private |
| ~Feat() | FT::Feat | inline |