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Get Help NowWe were unable to transcribe this image. build a linear regression model for “GRE score” and “chance of admit” from training data, . plot the regression line and the predicted points along the prediction line, . plot the true values from testing set and the residual line Use the following settings . figsize-(7,7), dpi-100 X axis is GRE score Y axis is chance of admit . Plot colors of your choice Sample output as shown in the following figure is for demonstration purposes only Training a simple linear regression model 1.0 0.9 ใน 0.8 D 0.7 0.5 0.4 300 320 290 310 330 340 x (GRE score) Training a simple linear regression model: true value and residual 0.9 0.8 0.7 E 0.6 0.5 0.4 290 300 310 320 330 340 X (GRE Score) Submission: Submit the following files to OnTrack: Your program source code (e.g. task5_2.py) A screen shot of your program running 1. 2. Check the following things before submitting Add proper comments to your code 1. Show transcribed image text
. build a linear regression model for “GRE score” and “chance of admit” from training data, . plot the regression line and the predicted points along the prediction line, . plot the true values from testing set and the residual line Use the following settings . figsize-(7,7), dpi-100 X axis is GRE score Y axis is chance of admit . Plot colors of your choice Sample output as shown in the following figure is for demonstration purposes only Training a simple linear regression model 1.0 0.9 ใน 0.8 D 0.7 0.5 0.4 300 320 290 310 330 340 x (GRE score)
Training a simple linear regression model: true value and residual 0.9 0.8 0.7 E 0.6 0.5 0.4 290 300 310 320 330 340 X (GRE Score) Submission: Submit the following files to OnTrack: Your program source code (e.g. task5_2.py) A screen shot of your program running 1. 2. Check the following things before submitting Add proper comments to your code 1.
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