Machine Learning

You will be aware of several algorithms. But how will you decide which machine learning algorithm to choose for your classifications problem?

You have built a multiple regression model. Your model R² isn’t as good as you wanted. For improvement, you remove the intercept term, your model R² becomes 0.8 from 0.3. Is it possible? How?

After analyzing the model, your manager has informed that your regression model is suffering from multicollinearity. How would you check if he’s true? Without losing any information, can you still build a better model?

How Can You Choose a Classifier Based on a Training Set Data Size?

The rise in global average temperature led to a decrease in the number of pirates around the world. Does that mean that the decrease in number of pirates caused climate change? (Hint- You should have understood that this is a classic ...

What Are Some Methods of Reducing Dimensionality? (Hint- Tell us about them, along with some practical examples)

After spending several hours, you are now anxious to build a high accuracy model. As a result, you build 5 GBM models, thinking a boosting algorithm would do the magic. Unfortunately, neither of the models could perform better than benchmark ...