Lead Data Scientist Question:
Tell me what is bias, variance trade off?
Answer:
Bias:
“Bias is error introduced in your model due to over simplification of machine learning algorithm.” It can lead to underfitting. When you train your model at that time model makes simplified assumptions to make the target function easier to understand.
Low bias machine learning algorithms - Decision Trees, k-NN and SVM
Hight bias machine learning algorithms - Liear Regression, Logistic Regression
Variance:
“Variance is error introduced in your model due to complex machine learning algorithm, your model learns noise also from the training dataset and performs bad on test dataset.” It can lead high sensitivity and overfitting.
“Bias is error introduced in your model due to over simplification of machine learning algorithm.” It can lead to underfitting. When you train your model at that time model makes simplified assumptions to make the target function easier to understand.
Low bias machine learning algorithms - Decision Trees, k-NN and SVM
Hight bias machine learning algorithms - Liear Regression, Logistic Regression
Variance:
“Variance is error introduced in your model due to complex machine learning algorithm, your model learns noise also from the training dataset and performs bad on test dataset.” It can lead high sensitivity and overfitting.
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