Basic concepts

Basic concepts

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- Statistical classification
- Guide to data mining

- Bias-variance tradeoff
- Scikit-Learn

- Principal component analysis
- Data Science For Business, What You Need to Know about Data Mining

- Data Mining with Weka
- Weko 3

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Basic concepts

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Open source, java, tools for data pre-processing, classification, regression, clustering, association rules, visualization

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Principles of popular algorithms

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Recommendation systems, classification, Naïve Bayes, clustering

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Classification, regression, clustering, dimensionality reduction, model selection, preprocessing, built on NumPy, SciPy, and matplotlib

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The problem of identifying to which of a set of categories a new observation belongs, on the basis of a training set of data containing observations whose category membership is known.

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The conflict in trying to simultaneously minimize these two sources of error that prevent supervised learning algorithms from generalizing beyond their training set

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k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster

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Phenomena that arise when analyzing and organizing data in high-dimensional spaces (often with hundreds or thousands of dimensions) that do not occur in low-dimensional settings

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Task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters)

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Dimensionality reduction, statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components, condense the information of a large set of correlated variables into a few variables

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a flowchart-like structure in which each internal node represents a "test" on an attribute, each branch represents the outcome of the test, and each leaf node represents a class label, the paths from root to leaf represent classification rules.

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A rule-based machine learning method for discovering interesting relations between variables in large databases

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Principles of popular algorithms

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Recommendation systems, classification, Naïve Bayes, clustering

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Classification, regression, clustering, dimensionality reduction, model selection, preprocessing, built on NumPy, SciPy, and matplotlib

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Open source, java, tools for data pre-processing, classification, regression, clustering, association rules, visualization

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