Modeling Bitcoin’s Market Capitalization
Bitcoin has been in news quite a bit lately with the price soaring. It was named the top performing currency four of the last five year. And it’ price has the…
Countvectorizer sklearn example
This countvectorizer sklearn example is from Pycon Dublin 2016. For further information please visit this link. The dataset is from UCI. In [2]: messages = [line.rstrip() for line in open('smsspamcollection/SMSSpamCollection')] In [3]: print (len(messages))…
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…
Regression in scikit-learn
We will compare several regression methods by using the same dataset. We will try to predict the price of a house as a function of its attributes. In [6]: import numpy…
k-Nearest Neighbors(kNN)
k-Nearest Neighbors(kNN) Pros: High accuracy, insensitive to outliers, no assumptions about data Cons: Computationally expensive, requires a lot of memory Works with: Numeric values, nominal values We have an existing…