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What is the difference between classification and prediction in machine learning?

nbro
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James
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    See: https://www.kdnuggets.com/faq/classification-vs-prediction.html and http://www.fharrell.com/post/classification/. – nbro Nov 03 '18 at 22:29

5 Answers5

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Classification is the prediction of a categorial variable within a predefined vocabulary based on training examples.

The prediction of numerical (continuous) variables is called regression.

In summary, classification is one kind of prediction, but there are others. Hence, prediction is a more general problem.

nbro
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Has QUIT--Anony-Mousse
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  • Even I had this doubt for quite some time. So in a broader sense, classification, regression all are different types of predictions right? – enigma6174 Jul 24 '19 at 01:51
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Functionality

  • Classification is about determining a (categorial) class (or label) for an element in a dataset

  • Prediction is about predicting a missing/unknown element(continuous value) of a dataset

Working Strategy

  • In classification, data is grouped into categories based on a training dataset.

  • In prediction, a classification/regression model is built to predict the outcome(continuous value)

Example

In a hospital, the grouping of patients based on their medical record or treatment outcome is considered classification, whereas, if you use a classification model to predict the treatment outcome for a new patient, it is considered a prediction.

Ali Akber
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Classification is the process of identifying the category or class label of the new observation to which it belongs. Predication is the process of identifying the missing or unavailable numerical data for a new observation. That is the key difference between classification and prediction. The predication does not concern about the class label like in classification.

Rubel
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Predictions can be using both regression as well as classification models. It means that once a model is trained on the training data; the next phase is to do predictions for the data whose real/ground-truth values are either unknown or kept aside to evaluate the performance of model. If the nature of the problem is of determining classes/labels/categories athen its classification and if the problem is about determining real numbers (numeric) values then its regression. In nutshell, predictions are supposed to done with both classification and regression for the test data set.

Mahdi
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1.Prediction is like saying something which may going to be happened in future.Prediction may be a kind of classification

2.Prediction is mostly based on our future assumptions

whereas

1.Classification is categorization of the things or data that we already have with us.This categorization can be based on any kind of technique or algorithms

2.Classification is mostly based on our current or past assumptions