Classification vs Regression

Classification vs. Regression

• Classification problem: predicting among two or more categories, also known as classes
  • Example1: Predict whether a patient has a liver disease or not
  • Example2: Predict whether the letter grade of a student (A,B,C,D or F)
• Regression problem: predicting a continuous (in other words, a number) value
  • Example1: Predict housing prices
  • Example2: Predict a student’s score in this course’s quiz2

In Classification problems we predict target value among two or more known categories.

For example:

• Whether a patient has a liver disease or not (2 possible target values)
• The letter grade of a student: A, B, C, D or F. (There are 5 categories)

Regression predicts a continuous (typically, floating-point) value.

For example:

• Housing prices
• The scores of students in this course’s quiz2.

Here are examples of classification and regression problems.

As we said before in a classification problem the target has discrete categories. In this example, our target has only two possible values; A+ or not A+. Our goal is to predict if a student will get a value of A+ or not A+.

In Regression problems, we are predicting each student’s grade, so the target here which is quiz2 contains the actual students’ score.

classification_df = pd.read_csv("data/quiz2-grade-toy-classification.csv")
classification_df.head()

	ml_experience	class_attendance	lab1	lab2	lab3	lab4	quiz1	quiz2
0	1	1	92	93	84	91	92	A+
1	1	0	94	90	80	83	91	not A+
2	0	0	78	85	83	80	80	not A+
3	0	1	91	94	92	91	89	A+
4	0	1	77	83	90	92	85	A+

We have created two toy datasets for classification and regression and this is our toy dataset for classification.

We can see in the first example, the target here is quiz2 and contains only 2 possible values; A+ or not A+.

regression_df = pd.read_csv("data/quiz2-grade-toy-regression.csv")
regression_df.head()

	ml_experience	class_attendance	lab1	lab2	lab3	lab4	quiz1	quiz2
0	1	1	92	93	84	91	92	90
1	1	0	94	90	80	83	91	84
2	0	0	78	85	83	80	80	82
3	0	1	91	94	92	91	89	92
4	0	1	77	83	90	92	85	90

On the other hand, in the regression problem, the target column (quiz2) contains the actual scores so we have continuous values in our quiz2 column.

Let’s apply what we learned!