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Statistical classification - Wikipedia

In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known

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Difference between classification and clustering in data mining? Ask Question 176 52 It is a common technique for statistical data analysis used in machine learning and data mining Classification is a process of categorization where objects are recognized, differentiated and understood on the basis of the training set of data

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Questions like this are a symptom of not truly understanding the difference between classification and regression and what accuracy is trying to measure 135 Responses to Difference Between Classification and Regression in Machine Learning Rizwan ali December 11, 2017 at 7:14 am # nice post to clear the basic concepts Reply

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Machine Learning: Classification Models – Fuzz – Medium

A classification model attempts to draw some conclusion from observed values Given one or more inputs a classification model will try to predict the value of one or more outcomes Outcomes are

Automated Text Classification Using Machine Learning

Automated Text Classification Using Machine Learning And, using machine learning to automate these tasks, just makes the whole process super-fast and efficient Artificial Intelligence and Machine learning are arguably the most beneficial technologies to have gained momentum in recent times They are finding applications everywhere

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Simple example of classifying text in R with machine

Simple example of classifying text in R with machine learning (text-mining library, caret, and bayesian generalized linear model) Classify tfidf tdm term document matrix - classifytextR

Classification - Oracle

Oracle Data Mining implements GLM for binary classification and for regression GLM provides extensive coefficient statistics and model statistics, as well as row diagnostics GLM also supports confidence bounds Support Vector Machine Support Vector Machine (SVM) is a powerful, state-of-the-art algorithm based on linear and nonlinear regression

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