User:Watereals/Books/CIT


 * Graph Theory
 * Graph theory
 * Graph (abstract data type)
 * Graph (mathematics)
 * Breadth-first search
 * Depth-first search
 * Shortest path problem
 * Dijkstra's algorithm
 * Bellman–Ford algorithm
 * Floyd–Warshall algorithm
 * Grover's algorithm
 * Prim's algorithm
 * Kruskal's algorithm
 * Connected component (graph theory)
 * Disjoint-set data structure
 * Dancing Links
 * A* search algorithm
 * IDA*


 * Search
 * Introduction to Algorithms
 * Search algorithm
 * Binary search algorithm
 * Uniform binary search
 * Ternary search
 * State space search
 * Incremental heuristic search
 * Nearest neighbor search
 * Depth-limited search
 * Best-first search
 * Fibonacci search technique
 * Bayesian search theory
 * Knuth's Algorithm X
 * Double hashing
 * Hash table
 * Linear hashing
 * Index mapping
 * Alpha–beta pruning
 * Linear search
 * Backtracking
 * God's algorithm
 * Perfect hash function
 * Hash function
 * K-independent hashing
 * Genetic algorithm
 * Geometric hashing
 * Locality-sensitive hashing


 * Machine learning
 * Data mining
 * Machine learning
 * Supervised learning
 * Binary classification
 * Statistical classification
 * Bayesian statistics
 * Bayes' theorem
 * Naive Bayes classifier
 * Probit model
 * Logistic regression
 * Multinomial logistic regression
 * Linear discriminant analysis
 * Artificial neural network
 * Perceptron
 * Support vector machine
 * Least squares support vector machine
 * Decision tree learning
 * Variable kernel density estimation
 * Random forest
 * K-nearest neighbors algorithm
 * Ensemble learning
 * Statistical relational learning
 * Classification rule
 * Boosting (machine learning)
 * Case-based reasoning
 * Learning vector quantization
 * Gene expression programming
 * Quadratic classifier
 * Unsupervised learning
 * Cluster analysis
 * K-means clustering
 * Mixture model
 * Hierarchical clustering
 * Hidden Markov model
 * Blind signal separation
 * Feature extraction
 * Dimensionality reduction
 * Principal component analysis
 * Independent component analysis
 * Non-negative matrix factorization
 * Singular value decomposition
 * Density estimation
 * Expectation–maximization algorithm
 * Semi-supervised learning
 * Co-training
 * Transduction (machine learning)
 * Inductive reasoning
 * Web search engine
 * Learning to rank
 * Recommender system
 * Metric (mathematics)
 * Data warehouse
 * Fuzzy logic