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## How do you predict a continuous variable?

**Regression Analysis**. **Regression analysis** is used to predict a continuous target variable from one or multiple independent variables. Typically, regression analysis is used with naturally-occurring variables, rather than variables that have been manipulated through experimentation.

## What is the difference between logistic regression and classification?

In a classification problem, the target variable(or output), y, can take only discrete values for given set of features(or inputs), X. Contrary to popular belief, logistic regression IS a regression model. … Logistic regression becomes a classification technique only when a decision threshold is brought into the picture.

## Which model works on continuous data?

A continuous response variable can be modeled using **ordinary least-squares regression (OLS regression)**, one of the GLM modeling techniques.

## How can we make a neural network to predict a continuous variable?

Ensure that your output vector for training and test data is exactly what you need, continuous for each element of output vector. Use what you said and familiar for the layers before the last layer. For the last layer use a dense layer with n, number of outputs, outputs each having linear activation, y = x.

## What is an example of regression problem?

Regression Predictive Modeling

For example, **a house may be predicted to sell for a specific dollar value**, perhaps in the range of $100,000 to $200,000. A regression problem requires the prediction of a quantity. … A problem with multiple input variables is often called a multivariate regression problem.

## Which model is best for regression?

**Statistical Methods for Finding the Best Regression Model**

- Adjusted R-squared and Predicted R-squared: Generally, you choose the models that have higher adjusted and predicted R-squared values. …
- P-values for the predictors: In regression, low p-values indicate terms that are statistically significant.

## What is a continuous dependent variable?

**If a variable can take on any value between its minimum value and its maximum value**, it is called a continuous variable; otherwise, it is called a discrete variable.

## Which technique is used to predict categorical responses?

Which technique is used to predict categorical responses? **Classification methods** are used to predict binary or multi class target variable.

## How do you convert regression to classification?

To add to the number of methods you can use to convert your regression problem into a classification problem, you can use **discretised percentiles** to define categories instead of numerical values. For example, from this you can then predict if the price is in the top 10th (20th, 30th, etc.) percentile.

## How do you explain Logistic Regression in interview?

The idea of Logistic Regression is to **find a relationship between features and probability of particular outcome**. E.g. When we have to predict if a student passes or fails in an exam when the number of hours spent studying is given as a feature, the response variable has two values, pass and fail.