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The best example of an ML classification algorithm is Email Spam Detector. The main goal of the Classification algorithm is to identify the category of a given dataset, and these algorithms are mainly used to predict the output for the categorical data.
Jan 24, 2024 · Machine Learning classification is a type of supervised learning technique where an algorithm is trained on a labeled dataset to predict the class or category of new, unseen data. The main objective of classification machine learning is to build a model that can accurately assign a label or category to a new observation based on its features.
Classification is a supervised machine learning method where the model tries to predict the correct label of a given input data. In classification, the model is fully trained using the training data, and then it is evaluated on test data before being used to perform prediction on new unseen data.
Apr 12, 2024 · Classification is a task of Machine Learning which assigns a label value to a specific class and then can identify a particular type to be of one kind or another. The most basic example can be of the mail spam filtration system where one can classify a mail as either “spam” or “not spam”.
Aug 19, 2020 · In machine learning, classification refers to a predictive modeling problem where a class label is predicted for a given example of input data. Examples of classification problems include: Given an example, classify if it is spam or not. Given a handwritten character, classify it as one of the known characters.
Mar 26, 2024 · Classification in machine learning is a type of supervised learning approach where the goal is to predict the category or class of an instance that are based on its features.
Nov 16, 2022 · Classification is the process of predicting the class of given data points. Classes are sometimes called targets, labels or categories. Classification predictive modeling is the task of approximating a mapping function (f) from input variables (X) to discrete output variables (y.)
