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<speak> If the output variable is a discrete value, <break strength="weak"/>you can call it a classification problem.<break strength="x-strong"/> In supervised, <break strength="weak"/>there are two types of algorithms. <break strength="strong"/>The first is regression algorithms, <break strength="weak"/>and the other is classification algorithms.<break strength="strong"/> If the output is continuous, <break strength="weak"/>we call it a regression. <break strength="x-strong"/> If the output is discrete, <break strength="weak"/>we call it classification. <break strength="strong"/>For regression, <break strength="weak"/>when you are going for Linear methods, <break strength="weak"/>the outliers are a big problem.<break strength="strong"/> We are approximating the relation between input and output using a curve. <break strength="x-strong"/> If outliers are present, <break strength="weak"/>curve fitting will be affected. <break strength="strong"/>You need to remove the outliers.<break strength="x-strong"/> In this case, <break strength="weak"/>you use the interquartile range method to filter out outliers. <break strength="strong"/>First, you have to identify the outliers. <break strength="strong"/>After that, <break strength="weak"/>you have to remove the outliers. <break strength="x-strong"/> First, <break strength="weak"/>let us see how to identify the outliers. <break strength="x-strong"/> Instead of using numerical methods, first, <break strength="weak"/>we will use graphical methods to detect outliers. <break strength="strong"/>For this, <break strength="weak"/>a boxplot is very useful.<break strength="strong"/> Pandas library has a boxplot method. <break strength="strong"/>Boxplot will take a column of that data frame. <break strength="x-strong"/> Draw boxplot for the column chance of admission. <break strength="strong"/>You see, in the boxplot, <break strength="weak"/>the upper region is 75%, and the lower region is 25%.<break strength="strong"/> If you see in the plot,<break strength="weak"/> there is a circle below the lower range. <break strength="strong"/>That means there is an outlier, and it less than the minimum value. <break strength="strong"/>There is an outlier on the other side. <break strength="strong"/>If circles are there outside the boundaries, <break strength="weak"/>we call them outliers.<break strength="strong"/> In the chance of admit, there are outliers. <break strength="strong"/>We do not know the number of outliers. <break strength="strong"/>But we know that there are outliers in the chance of admit column.<break strength="strong"/> Next, draw a boxplot of the GRE score and the Toefl score <break strength="x-strong"/> </speak>