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6 years ago in Research Writing By Buchiramulu Batta

Important algorithms in ML

Hello all! I’m interested in machine learning domain and am planning to conduct research in this area. I know that there are plenty of algorithms in machine learning language. But which of them are popular and a must for researchers to know in this field? Suggestions please!

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By Krishan Pancholi Answered 6 years ago

There are 3 most important algorithms in machine learning domain. They are:
1. Supervised learning – in this type of algorithm, machine maps or assigns the given input to the output. And the output for a given input is known in advance. Here regression and classification problems are solved, labelled data is used for training and this algorithm is mainly used to predict modelling. The popular algorithms used here are linear regression, SVM, neural networks, and decision trees.
2. Semi-supervised learning – these lie between supervised and unsupervised learning. It is used in the real-world (to produce the desired results) where the data collected are a combination of labelled and unlabeled data.
3. Unsupervised learning – here the output for a given inputs is unknown. It is used in clustering problems and anomaly detection. Here unlabeled data is used and is used for descriptive modelling. The popular algorithms used here are association rule and k-means clustering.

By Buchiramulu Batta Answered 6 years ago

Any other algorithms?

By Suresh Answered 6 years ago

You have to learn logistics regression and least square regression. Logistic regression measures the relationship between the one or more independent variables and categorical dependent variable.

By Krishan Pancholi Answered 6 years ago

Suresh, logistic regression and least square regression are not separate algorithms. Instead they are the part of supervised learning algorithm.

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