1. Use the Boston data set available in sklearn package. Perform exploratory data analysis and construct a linear regression to predict the house price. You can use the following Python code to load the dataset.
import pandas as pd # conventional alias
from [login to view URL] import load_boston
dataset = load_boston()
df = [login to view URL]([login to view URL], columns=[login to view URL]
[login to view URL] to the following link of Iris data set.
[login to view URL] where you can download the data set. You goal is to set-up and train a classifier. You are required to show the steps in preparing the data set, perform exploratory data analysis, identify the classifier suitable for this task. Read about confusion matrix and present the confusion matrix for your trained algorithm.
[login to view URL] Sigmoid function / Softmax function is used in classification?Now observe the following function in Figure Q1 and state if it can be used in place of the sigmoid function for binary classification.
Please see the figure in the uploaded doc
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I am a Python Data Analytics Professional and trainer , I've gone through the Boston data a couple of time. You can proceed with further details in the chat box