95. What are the assumptions of linear regression? Several linear regression assumptions are baked into the dataset, as well as how the model is built. Otherwise, if these assumptions are violated, we become privy to the phrase “garbage in, garbage out.” The first assumption is that there...
6. What is Linear Regression in Machine Learning? 7. What is a Decision Tree in Machine Learning? 8. What are the types of Machine Learning? 9. What is Bayes’s Theorem in Machine Learning? 10. What is PCA in Machine Learning? Basic Machine Learning Interview Questions 1. What is Bias...
For example, in data science, models like linear or logistic regression will miss something important about the data and end up with prediction bias. It’s like putting blinders on the horses; they only see straight ahead thus accuracy is reduced due to simplified assumptions. Want to know abo...
Answer to: Answer the following True or False questions based on linear regression model. By signing up, you'll get thousands of step-by-step...
These are only two of the core methods used to detect outliers. Other approaches include linear regression models, information theoretic models, high-dimensional outlier detection methods and other approaches. 33. What is the FSCK command used for?
kernlab—provides kernel-based methods for classification, regression, and clustering algorithms. randomForest—for random forest classification and regression algorithms. xgboost—for gradient boosting, linear regression, and decision tree algorithms. rpart—for recursive partitioning in classification, regressio...
Q: What are the assumptions required for linear regression? There are four major assumptions: There is a linear relationship between the dependent variables and the regressors, meaning the model you are creating actually fits the data The errors or residuals of the data are normally distr...
1. A linear regression gives the following output: Figures in square brackets are estimated standard errors of the coefficient estimates. What is the value of the test statistic for the hypothesis that the coefficient of is zero against the alternative that is less than zero?
This is same as the normal distribution, but with a average of ‘0’ and SD is equal to ‘1. Q28). Reasons for using Regression? Regression is powerful. It’s versatile because it can be used for all kinds of data, including non-linear relationships. In fact, regression can be really...
You can also find all 50 answers here 👉 Devinterview.io - Logistic Regression 1. What is logistic regression and how does it differ from linear regression? Logistic Regression is designed to deal with binary classification tasks. Unlike Linear Regression, it doesn’t use a direct linear mappi...