## 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:UserspiushDesktopDatasetTitanictrain.csv') In [363]: df_train.head(2) Out[363]: PassengerId Survived Pclass Name Sex Age…

## 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?…

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…

## Apriori Algorithm (Python 3.0)

Apriori Algorithm The Apriori algorithm principle says that if an itemset is frequent, then all of its subsets are frequent.this means that if {0,1} is frequent, then {0} and {1}…

## Principal Component Analysis in scikit-learn

Principal Component Analysis (PCA) is an orthogonal linear transformation that turns a set of possibly correlated variables into a new set of variables that are as uncorrelated as possible. The…

## Naiive Bayes in scikit-learn

Naïve Bayes is a simple but powerful classifier based on a probabilistic model derived from the Bayes' theorem. Basically it determines the probability that an instance belongs to a class…

## Decision Trees in scikit-learn

Decision trees are very simple yet powerful supervised learning methods, which constructs a decision tree model, which will be used to make predictions. The main advantage of this model is…

## Support Vector Machine in scikit-learn

Support Vector Machines has become one of the state-of-the-art machine learning models for many tasks with excellent results in many practical applications. One of the greatest advantages of Support Vector…