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Showing 41 - 42 results of 42 for search '((hang OR ((chang OR chuang) OR chans)) OR (((((changs OR chuangs) OR (changs OR chuangs)) OR (changs OR chuangs)) OR chong) OR chain)) 'em high', query time: 0.24s Refine Results
  1. 41
    EW 104 : EW against a new generation of threats / EW against a new generation of threats

    EW 104 : EW against a new generation of threats / EW against a new generation of threats by Adamy, David

    Published 2015
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  2. 42
    Mastering Java Machine Learning.

    Mastering Java Machine Learning. by Kamath, Dr. Uday

    Published 2017
    Table of Contents: “…Case Study -- Horse Colic Classification -- Business problem -- Machine learning mapping -- Data analysis -- Label analysis -- Features analysis -- Supervised learning experiments -- Weka experiments -- RapidMiner experiments -- Results, observations, and analysis -- Summary -- References -- Chapter 3: Unsupervised Machine Learning Techniques -- Issues in common with supervised learning -- Issues specific to unsupervised learning -- Feature analysis and dimensionality reduction -- Notation -- Linear methods -- Principal component analysis (PCA) -- Random projections (RP) -- Multidimensional Scaling (MDS) -- Nonlinear methods -- Kernel Principal Component Analysis (KPCA) -- Manifold learning -- Clustering -- Clustering algorithms -- k-Means -- DBSCAN -- Mean shift -- Expectation maximization (EM) or Gaussian mixture modeling (GMM) -- Hierarchical clustering -- Self-organizing maps (SOM) -- Spectral clustering -- Affinity propagation -- Clustering validation and evaluation -- Internal evaluation measures -- External evaluation measures -- Outlier or anomaly detection -- Outlier algorithms -- Statistical-based -- Distance-based methods -- Density-based methods -- Clustering-based methods -- High-dimensional-based methods -- One-class SVM -- Outlier evaluation techniques -- Supervised evaluation -- Unsupervised evaluation -- Real-world case study -- Tools and software -- Business problem -- Machine learning mapping -- Data collection -- Data quality analysis -- Data sampling and transformation -- Feature analysis and dimensionality reduction -- Observations on feature analysis and dimensionality reduction -- Clustering models, results, and evaluation -- Observations and clustering analysis -- Outlier models, results, and evaluation -- Summary -- References -- Chapter 4: Semi-Supervised and Active Learning -- Semi-supervised learning.…”
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