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How do you choose target variable?
In general, the target variable should have a fairly uniform distribution; in the binary case, as close to a 50/50 split as possible. If the variable is skewed to either side, it will be harder for the model to evaluate the other predictor variables. If your distribution is uneven, consider oversampling your data.
Should I scale target variable?
Yes, you do need to scale the target variable. I will quote this reference: A target variable with a large spread of values, in turn, may result in large error gradient values causing weight values to change dramatically, making the learning process unstable.
Which one is used for continuous target variables?
Linear regression
Linear regression is to be used when the target variable is continuous and the dependent variable(s) is continuous or a mixture of continuous and categorical, and the relationship between the independent variable and dependent variables are linear.
What do you call problem with multiple target variables?
F o r classification models, a problem with multiple target variables is called multi-label classification. In the realm of regression models, as a beginner, I found the nomenclature a bit confusing.
Why is it important to know target variable?
It’s important to understand the characteristics of your target variable before you begin running models and forming predictions.
Can a regression model support multiple target variables?
Multi Target Regression Machine Learning classifiers usually support a single target variable. In the case of regression models, the target is real valued, whereas in a classification model, the target is binary or multivalued. F o r classification models, a problem with multiple target variables is called multi-label classification.
How are target variables used in supervised classification?
A walk down the tree (starting from the root and then down to a leaf node) can be compared to moving from a large cluster (at the top) to smaller and smaller clusters as we near the leaf nodes. In supervised classification, the distance measure is the class of the target variable.