In data science, we work with data to produce insights that can help businesses solve problems. In real-world applications, most of the data is produced in a categorical format. Most of the attributes like gender, day of the week, names, etc can only be presented in textual or categorical format. On the contrary, most of…
We use different algorithms to perform market basket analysis in data mining. For this, we use the apriori algorithm, fp-growth algorithm, and the ECLAT algorithm to find frequent item sets and association rules. This article will discuss how to implement the apriori algorithm in Python. How to Implement Apriori Algorithm in Python? To implement the…
We use different algorithms in market basket analysis to find frequent itemsets. In this article, we will discuss the Equivalence Class Clustering and bottom-up Lattice Traversal (ECLAT) algorithm. Here, we will discuss the basics of the Eclat algorithm with a numerical example. We will also discuss the advantages and disadvantages of the ECLAT algorithm over…
Linear regression and logistic regression are two of the simplest machine learning algorithms. This article discusses linear regression vs logistic regression with examples to find the similarities and differences between the two algorithms. Linear Regression vs Logistic Regression in Machine Learning Before getting into the details, let us first look at a summary of linear…
We use classification and regression algorithms for supervised learning tasks in machine learning. We use both these algorithms to predict a class or a target value for a new data point if we are given labeled training data. This article discusses classification vs regression including their objective functions to analyze how similar or different these…
We use classification and clustering algorithms in machine learning for supervised and unsupervised tasks respectively. In this article, we will discuss clustering vs classification in machine learning to discuss the similarities and differences between the two tasks using examples. What is Clustering in Machine Learning? Clustering is an unsupervised machine-learning task. In clustering, we try…
The FP Growth algorithm is a frequent pattern mining algorithm used in market basket analysis. This article discusses the FP growth algorithm with a step-by-step numerical example. What is the FP Growth Algorithm? Like the apriori algorithm, the FP-Growth algorithm is also used for frequent pattern mining. The FP-Growth or Frequent Pattern Growth algorithm is…
The Apriori algorithm is one of the first algorithms used for association rule mining. In this article, we will discuss the basics of the apriori algorithm using a numerical example. Here, we will use a sample transaction dataset to obtain frequent itemsets and create association rules using the apriori algorithm. We will also discuss the…
Market basket analysis is used by businesses to implement effective sales strategies. Association rule mining is one of the most important steps in market basket analysis. This article discusses the basics of association mining with different examples to describe terms like support, lift, and confidence. What is An Association Rule? As the name suggests, the…
The K-nearest neighbors and the k-means clustering algorithm are two of the most used machine learning algorithms. This article discusses the differences and similarities of the KNN vs KMeans algorithm. KNN vs KMeans: Summary Table If you want a quick snapshot of the differences between KNN and the K-means clustering algorithm, you can have a…