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MACHINE LEARNING (Classification/Regression (Performance Evaluation (Cross…
MACHINE LEARNING
Classification/Regression
Training/Test set
Accuracy/MSE
Performance Evaluation
Training Error
Generalization Error
Overfitting/Underfitting
Holdout/Iterated Holdout
Cross Validation
K Folds
LOOCV
Comparing Classifier
IC
Accuracy/MSE
Hypothesis Testing
Class Imbalance Problem
Cost
Cost Matrix
Cumulative Gains
Lift Factor
Lift Chart
ROC curve
Data
Types
Nominal
Ordinal
Interval
Ratio
Discrete
Continuos
Exploration
Summary Statistics
Visualization
Missing Replacement
Removal
Mean-Mode
Most Probable
Preprocessing
Aggregation
Sampling
Dimensionality reduction
Binarization/Discretization
Variable Transformation
Feature Selection
Redundant/Irrelevant attributes
Approches
Brute-Force
Embedded
Filter
Wrapper
Feature Creation
Clustering
Cluster analysis
Similarity
Dissimilarity
Proximity
Mahlanobis
Correlation
Cosine Similarity
Minkowski
Simple Matching Coefficient
Jaccard
Types
Exclusive/Overlapping/Fuzzy
Partitional/Hierarchical
Complete/Partial
Algorithms
K-Means
Fuzzy C-Means
Dendograms
SOMS
DBSCAN
Graph Based
Association Analysis
Frequent Itemset
Candidate Itemset
Apriori Principle
Support Based Pruning
Maximal Frequent Itemset
Closed Frequent Itemset
Redundant Association Rule
Evaluation
Interesting/Uninteristing Association Rule
Lift
Interest Factor
Correlation Analysis
IS Measure
Symmetric and Asymmetric Objective Measures
Selection of Objective Measures
Simposon's Paradox