Man pages for jakubkala/QuiPTsim
| accuracy | Accuracy (fraction of correctly classified obesravtions) |
| add_motifs | injects motifs to a sequence |
| aggregate_metrics | Aggregates metrics |
| aggregate_results | aggregates results from 'parse_results' |
| benchmark_summary | Function summarizes results for a given feature selection... |
| build_model | function builds a model and predicts out of fold probabilites |
| calculate_ngram_prob | function computes probability of given n-gram |
| calculate_score | Calculates metrics for a given feature selection method |
| calculate_seq_prob | function computes probability of given sequence |
| collect_filtering_times | function aggregates computation times |
| compute_metrics | Aggregated scores |
| cosine_similarity | calculates cosine similarity of two vectors |
| count_ngrams | wrapper for seqR counters |
| create_benchmark_data | Computes feature selection on n-gram matrices Result is an... |
| create_simulation_data | function generates set of RDS files containing n-gram... |
| create_simulation_data_set_of_motifs | function generates set of RDS files containing n-gram... |
| euclidean_norm | calculates euclidean norm of a given vector |
| evaluate_filtering_results | Wrapper for 'evaluate_selected_kmers' functions |
| evaluate_models | Function trains and evaluates model on selected k-mers |
| evaluate_selected_kmers | Evaluation of filtered k-mers in ranking model approach |
| F1score | F1-score (harmonic mean of precision and recall) |
| filter_ngrams | Wrapper for feature selection methods |
| filter_nonrankings | function that evaluates nonranking methods |
| filter_nonrankings_exp3 | function that evaluates nonranking methods |
| filter_rankings | function creates and evaluates filtering rankings |
| filter_rankings_exp3 | function creates and evaluates filtering rankings |
| generate_motifs | generate multiple motifs from alphabet |
| generate_probs | function generates two vectors of probabilities with given... |
| generate_sequences | function counts n-grams in given sequences |
| generate_single_motif | function generates motif from an alphabet TODO: motif length... |
| kmers_for_nonranking_methods | calculates number of k-mers to select for non-ranking methods |
| parse_results | parsing filtering results for ranking methods |
| positive_ngrams | Function returns ector indicating n-grams considered positive |
| precision | Precision |
| QuiPTsimBenchmark | Function wraps up QuiPT evaluation auxiliary functions |
| rbind_ngram_matrices | function binds n-gram matrices |
| rbind_ngrams | function combines two ngram matrices |
| read_ngram_matrix | function reads output files of 'create_simulation_data' |
| read_simulation_data | function reads results of 'create_simulation_data' function... |
| recall | Recall |
| sensitivity | Sensitivity (true positive rate, recall) |
| sequenceTransitionMatrix | function computes transition matrix |
| simulate_sequences | function generates sequences (both positive & negative) |
| simulate_single_sequence | generates sequence of elements from alphabet with replacement |
| specificity | Specificity (true negative rate) |
| subset_matrix | subsets simple triplet matrix |
| validate_motifs | function validates if given motifs can be injected to a... |
