Sspyinspml.hashnode.dev·Jan 5, 2024 · 2 min readLogistic Regression# Logistic Regression # Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd # Importing the dataset dataset = pd.read_csv('Social_Network_Ads.csv') X = dataset.iloc[:, [2, 3]].values y = dataset.iloc[:, 4]...00
Sspyinspml.hashnode.dev·Jan 5, 2024 · 1 min readMultiple linear Regressionimport numpy as np import pandas as pd dataset = pd.read_csv('50_Startups.csv') X = dataset.iloc[:, :-1] y = dataset.iloc[:, 4] states=pd.get_dummies(X['State'],drop_first=True) X=X.drop('State',axis=1) X=pd.concat([states,X],axis=1) from sklearn.mod...00
Sspyinspml.hashnode.dev·Jan 5, 2024 · 1 min readAppori Algorithmimport numpy as np import matplotlib.pyplot as plt import pandas as pd dataset = pd.read_csv('Market_Basket_Optimisation.csv', low_memory=False, header=None) !pip install apyori list_of_transactions = [] for i in range(0, 7501): list_of_transactions....00
Sspyinspml.hashnode.dev·Jan 5, 2024 · 1 min readCART Decisionsfrom sklearn import tree from sklearn.datasets import load_iris iris = load_iris() clf = tree.DecisionTreeClassifier() clf = clf.fit(iris.data, iris.target) import graphviz dot_data = tree.export_graphviz(clf, out_file=None) graph = graphviz.Sour...00
Sspyinspml.hashnode.dev·Jan 5, 2024 · 1 min readK means clustering#22.K-Means Clustering from sklearn.datasets import load_iris from itertools import cycle from sklearn.decomposition import PCA from sklearn.cluster import KMeans from numpy.random import RandomState import pylab as pl import matplotlib.pyplot as pl...00