Womens Health Risk Assessment
Competition Notes, Machine Learning, scikit-learn

Modeling Women’s Health Risk Assessment

Women’s Health Risk Assessment is a multi-class classification competition for finding an optimized machine learning a solution that allows a young woman (age 15-30 years old) to be accurately categorized for their particular health risk. Based on the category a patient falls within, healthcare providers can offer appropriate education and training programs to help reduce the patient’s reproductive health risks.…

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Installing XGBoost for Windows
Data Analysis Resources, Machine Learning, scikit-learn

Installing XGBoost for Windows – walk-through

I have the following specification on my computer: Windows10, 64 bit,Python 3.5 and Anaconda3.I tried many times to install XGBoost but somehow it never worked for me. Today I decided to make it happen and am sharing this post to help anyone else who is struggling with installing XGBoost for Windows. XGBoost is short for “Extreme Gradient Boosting”.XGBoost is an…

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Kaggle, Machine Learning, scikit-learn

Evaluating Algorithms using Kaggle’s Digit Recognizer Data

In [1]: import numpy as np import pandas as pd import seaborn as sns import matplotlib.pyplot as plt %matplotlib inline import warnings warnings.filterwarnings(‘ignore’) In [2]: # importing the train dataset train = pd.read_csv(r’C:\Users\piush\Desktop\Dataset\DigitRecognizer\train.csv’) train.head(10) Out[2]: label pixel0 pixel1 pixel2 pixel3 pixel4 pixel5 pixel6 pixel7 pixel8 … pixel774 pixel775 pixel776 pixel777 pixel778 pixel779 pixel780 pixel781 pixel782 pixel783 0 1 0 0 0 0…

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Submission for Kaggle's Titanic Competition
Kaggle, Machine Learning, Predictive Analysis

Submission for Kaggle’s Titanic Competition

Following is my submission for Kaggle’s Titanic Competition In [361]: import pandas as pd import numpy as np In [362]: df_train = pd.read_csv(r’C:\Users\piush\Desktop\Dataset\Titanic\train.csv’) In [363]: df_train.head(2) Out[363]: PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare Cabin Embarked 0 1 0 3 Braund, Mr. Owen Harris male 22.0 1 0 A/5 21171 7.2500 NaN S 1 2 1 1 Cumings, Mrs. John…

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FP-growth algorithm
Machine Learning

Coding FP-growth algorithm in Python 3

FP-growth algorithm Have you ever gone to a search engine, typed in a word or part of a word, and the search engine automatically completed the search term for you? Perhaps it recommended something you didn’t even know existed, and you searched for that instead. This requires a way to find frequent itemsets efficiently. FP-growth algorithm find frequent itemsets or…

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Machine Learning

AdaBoost (Python 3)

AdaBoost The AdaBoost (adaptive boosting) algorithm was proposed in 1995 by Yoav Freund and Robert Shapire as a general method for generating a strong classifier out of a set of weak classifiers . AdaBoost works even when the classifiers come from a continuum of potential classifiers (such as neural networks, linear discriminants, etc.) AdaBoost Pros: Low generalization error, easy to…

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