Final Updates

README.md

@@ -23,13 +23,17 @@ Logistic regression estimates the probability of an event occurring, such as vot
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 <p align="center"><img src="https://thumbs.gfycat.com/RaggedShorttermHalcyon-size_restricted.gif" width="400"></p>
 
+<p align="center"><img src="data:image/png;base64,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" width="150"></p>
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 ## Why have I used logistic regression in this project?
 Logistic Regression is used when the dependent variable(target) is categorical, such as to predict whether the tumor is malignant (1) or benign (0).
 
 ## Why I found Logistic Regression to be preferrable in this project?
 Logistic regression analysis is valuable for predicting the likelihood of an event. It helps determine the probabilities between any two classes by analyzing or training on historical data.
 
+<p align="center"><img src="https://www.saedsayad.com/images/LogReg_1.png"></p>
+
 ## Dataset
 I am importing the classified breast cancer wisconsin dataset.
 The breast cancer dataset is a classic and very easy binary classification dataset.

breastcancerdetection.py

@@ -1,10 +1,10 @@
 # Importing libraries
-import numpy as np
 from sklearn import datasets
 import pandas as pd
 from sklearn.model_selection import train_test_split
 from sklearn.linear_model import LogisticRegression
 from sklearn.metrics import accuracy_score
+import numpy as np
 
 # Fetching the dataset
 breast_cancer = datasets.load_breast_cancer()