Support Vector Machines (SVM) |
92 |
Manually Curated |
56 |
Random Forest |
28 |
Text Mining |
26 |
Hypergeometric Test |
13 |
Linear Regression Analysis |
12 |
Survival Analysis |
10 |
k-Nearest Neighbour (kNN) |
10 |
k-Means |
9 |
Meta-analysis |
9 |
Artificial Neural Network (ANN) |
9 |
Hidden Markov Model (HMM) |
9 |
LASSO |
8 |
Mutual Information |
8 |
Random Walk |
7 |
Boosting |
7 |
Principal Component Analysis (PCA) |
6 |
Naive Bayes |
6 |
Dynamic Programming Algorithms |
6 |
Hierarchical Clustering |
6 |
Logistic Regression |
6 |
Entropy |
5 |
Expectation Maximisation (EM) |
5 |
Analysis of Variance (ANOVA) |
5 |
Self-Organizing Map (SOM) |
5 |
Smith-Waterman Algorithm |
5 |
C4.5 |
4 |
Bayesian Network (BN) |
4 |
Decision Tree |
4 |
Information Gain |
4 |
AdaBoost |
3 |
Convolutional Neural Network (CNN) |
3 |
Semantic |
3 |
Biclustering |
3 |
Burrows-Wheeler Transform (BWT) |
2 |
SVM-RFE |
2 |
Minimal Redundancy Maximal Relevance (MRMR) |
2 |
Bayesian Inference |
2 |
Genetic Algorithms (GA) |
2 |
Bayesian Statistics |
2 |
Non-negative Matrix Factorization (NMF) |
2 |
Support Vector Regression (SVR) |
2 |
Markov Cluster (MCL) |
2 |
Penalized Generalized Estimating Equations (PGEE) |
1 |
Markov Model |
1 |
k-Medians |
1 |
Markov-Chain Monte-Carlo Methods (MCMC) |
1 |
Fisher's Exact Test |
1 |
Complete-linkage Clustering |
1 |
FP-growth Algorithm |
1 |
Kemeny Optimal Aggregation (KOA) |
1 |
Wang-Landau Monte Carlo Methods |
1 |
Conditional Random Fields (CRFs) |
1 |
Gaussian Naive Bayes |
1 |
Kolmogorov–Smirnov Test |
1 |
Molecular Dynamics |
1 |
Grid Search Method (PGS) |
1 |
Semi-Automatic Extraction |
1 |
Deep Belief Network (DBN) |
1 |
Singular Value Decomposition (SVD) |
1 |
Betweenness Centrality Clustering (BCC) |
1 |
Literature-based Discovery |
1 |
Bicliques Merging |
1 |
Empirical Algorithmics |
1 |
PageRank |
1 |
Empirical Bayes Methods |
1 |
Particle Swarm Optimization (PSO) |
1 |