The Comprehensive Guide for Feature Engineering
Feature Engineering is the art/science of representing data is the best way possible. This is the comprehensive guide for Feature Engineering for myself but I figured that they might be…
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…
Evaluating Algorithms using MNIST
This post is evaluating Aagorithms using MNIST 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]:…
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 (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…
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…