Machine Learning Technique Which Is Used To Predict A Continuous Output Variable

It is used for predicting the continuous dependent variable with the help of independent variables. Basically predicting a continuous variable is termed as regression.

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BACKGROUND OF MACHINE LEARNING The machine learning.

Machine learning technique which is used to predict a continuous output variable. Linear regression as the name says finds a linear curve solution to every problem. There are a no of regression algorithms like ridge and lasso regression you may want to check out. Linear Regression is one of the most simple Machine learning algorithm that comes under Supervised Learning technique and used for solving regression problems.

Until now we only considered methods that can help us predict class labels. This subject is the first compulsory. If you want to start machine learning Linear regression is the best place to start.

Start reviewing the literature you will find a. A random forest will work however standard regression will also work with categorical variables as predictors. Machine Learning subject having subject no- 410250 the first compulsory subject of 8 th semester and has 3 credits in the course according to the new credit system.

Machine Learning being the most prominent areas of the era finds its place in the curriculum of many universities or institutes among which is Savitribai Phule Pune UniversitySPPU. SSE Y f X2 S S E Y f X 2. Linear regression uses weights and minimises the residual sum of squares between the actual and outcome variable Y and the predictor variables denoted as x.

Regression is the type of Supervised Learning in which labelled data used and this data is used to make predictions in a continuous form. Regression with machine learning. View machine learning techniqueediteddocx from CS 489 at Shaheed Zulfikar Ali Bhutto Institute of Science Technology Karachi.

Linear Regression is a regression model meaning itll take features and predict a continuous output eg. When doing classification in scikit-learn y is a vector of integers or strings. On the other hand if the goal is to predict a continuous target variable it is said to be a regression task.

You will have to one-hot encode your categorical predictors into 6 dummy variables classes-1 7-1 6. However all the methods we have shown can also be used to predict continuous variables. In this case the methods will try to optimize the prediction in error which is usually in the form of the sum of squared errors SSE.

Then there is MARS Multivariate Adaptive Regression Splines and gamma regression.

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