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RF, Adabost.M1, DecisionTree, Logistic Abnormalcy , Unworldly Bayes, Neuronic Fabric, CNN, K-mean , Unsubdivided retrogress

Requirements

No Prior programing noesis is required. Nevertheless a extremum knowledge of any planning and staple statistics is a nonnegative

Description

How to download and establish R
How to set your working directory implication your data and find rows containing missing values
For binary arrangement
Preparation and reasoning using the Ergodic Timber sit , foretelling accuracy, Disarray matrix and certainty distance
Breeding and reasoning using the Adabost.M1 help , forecasting accuracy, Embarrassment matrix and certainty separation
Breeding and anticipation using the Mind Actor hypothesis , prevision truth, Disarray matrix and confidence separation
Breeding and prediction using the logistic abnormality assistant, foretelling truth, fault matrix and friendship separation
Grooming and prediction using the Naive Mathematician pattern, prediction accuracy, mistake matrix and sureness measure
Grooming and prognostication using the System Material worthy , forecasting accuracy, mistake matrix and sureness separation
Breeding and prediction using the Convolutional neuronic web (KNN) , prediction accuracy, disarray matrix and confidence distance
How to commix models to promise
Nonexistent values communicating ,variables option and prevision using a lineal reversal model
K convey Clustering

Who this bed is for:

If you are fascinated on prognosticative analytic , then this class is a reactionary fit for you.

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