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CSA3180: Natural Language Processing

CSA3180: Natural Language Processing

CSA3180: Natural Language Processing. Classification I Discovering Word Associations Text Classification TF.IDF Clustering/Data Mining Linear and Non-Linear Classification Binary Classification Multi-Class Classification. Introduction.

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964 views • 82 slides
Ch12 Analysis of Variance

Ch12 Analysis of Variance

Ch12 Analysis of Variance. Outline. Completely randomized designs Randomized-block designs. Analysis of Variance. Single Factor Analysis of Variance Single Factor ANOVA One Way Analysis of Variance One Way ANOVA. Background.

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555 views • 42 slides
Assumptions of the ANOVA

Assumptions of the ANOVA

Assumptions of the ANOVA. The error terms are randomly, independently, and normally distributed, with a mean of zero and a common variance. There should be no systematic patterns among the residuals The distribution of residuals should be symmetric (not skewed)

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745 views • 40 slides
LECTURE 15: SUPPORT VECTOR MACHINES

LECTURE 15: SUPPORT VECTOR MACHINES

LECTURE 15: SUPPORT VECTOR MACHINES. Objectives: Empirical Risk Minimization Large-Margin Classifiers Soft Margin Classifiers SVM Training Relevance Vector Machines Resources: DML: Introduction to SVMs AM: SVM Tutorial JP: SVM Resources OC: Taxonomy NC: SVM Tutorial. Class 2. Class 1.

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693 views • 12 slides
LECTURE 16: SUPPORT VECTOR MACHINES

LECTURE 16: SUPPORT VECTOR MACHINES

LECTURE 16: SUPPORT VECTOR MACHINES. Objectives: Empirical Risk Minimization Large-Margin Classifiers Soft Margin Classifiers SVM Training Relevance Vector Machines Resources: DML: Introduction to SVMs AM: SVM Tutorial JP: SVM Resources OC: Taxonomy NC: SVM Tutorial. Class 2. Class 1.

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224 views • 12 slides

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