Category: Classification Algorithms
-
How to Evaluate Your Classification Algorithm in Python
In the previous episode, we went over the different methods you can evaluate your classification algorithm. In this episode, we focus on applying these methods in Python. You can view and use the code and data used in this episode here: Link 1. Building the Classification Algorithm First we need to build a classification algorithm…
-
Evaluation of Classification Algorithms
There are various classification algorithms such as: Support Vector Machines (Episode 9.1) Logistic Regression (Episode 7.1) Decision Trees (Soon to come) But how do we evaluate these algorithms’ performance? In this episode we look at the following evaluation metrics: Accuracy, Precision, Recall (True Positive Rate), False Positive Rate, Specificity, Sensitivity, F1 score. AUROC Score (Area…
-
Non-linear Support Vector Machines in Python
Code and data used can be found here: Repository An explanation of Non-linear support vector machines: Episode 9.3 How to set up your programming environment can be found at the start of :Episode 4.3 Objective Produce a non-linear support vector machine that is able to correctly classify a pulsar star. Importing and exploring our Data We have…
-
Non-linear Support Vector Machines Explained
In the previous episode we explained what are support vector machines and the maths behind the algorithm. In this episode we discuss support vector machines for non-linearly separable data. SVMs for non-linearly separable data What if the data is not linearly separable? For example: Calculating a non-linear support vector machine may overfit our data: In…
-
Linear Support Vector Machines in Python
Code and data used can be found here: Repository An explanation of Non-linear Support Vector Machines: Episode 9.3 Please consider watching this video if any section of this article is unclear. How to set up your programming environment can be found at the start of : Episode 4.3 Objective Produce a linear support vector machine that…
-
Support Vector Machines Explained
What are Support Vector Machines? Support Vector machines are a common supervised machine learning algorithm used in both classification and regression problems, however are most commonly used for classification which will be the focus for this article. Overview The job of a support vector machine for classification problems is take labelled data such as the…
-
Logistic Regression in Python
You can view and use the code and data used in this episode here: Link Consider reading Episode 7.1 before continuing, which explains how logistic regression works. How to set up your programming environment can be found at the start of : Episode 4.3 Objective Predict whether it will rain tomorrow in Albury, Australia given the…
-
Logistic Regression Explained
Logistic Regression can be thought of as an extension of Linear Regression. With Linear Regression our final output for our model took a single value, however, with logistic regression, we apply an extra function to Linear Regression that puts our final value output into a group i.e. 1 or 0. What is Logistic Regression? Logistic…
The Data Series 