case study
k-Nearest Neighbors Classification algorithm [Case Study]
Predicting car quality with the help of Neighbors Introduction : The goal of the blogpost is to get the beginners started with fundamental concepts of the K Nearest Neighbour Classification Algorithm popularly known by the name KNN classifiers. We will mainly focus on learning to build your first KNN model. The data cleaning and preprocessing parts would be covered in detail in an upcoming post. Classification Machine Learning is a technique of learning where a particular instance is mapped against one of the many labels. The labels are prespecified to train your model . The machine learns the pattern from the data in such a way that the learned representation successfully maps the original dimension to the suggested label/class without any more intervention from a human expert. How does...
K-Means model for Predicting Car quality[Case Study]
Problem Statement : To build a simple K-Means model for clustering the car data into different groups. Data details ========================================== 1. Title: Car Evaluation Database========================================== The dataset is available at “http://archive.ics.uci.edu/ml/datasets/Car+Evaluation” 2. Sources: (a) Creator: Marko Bohanec (b) Donors: Marko Bohanec (marko.bohanec@ijs.si) Blaz Zupan (blaz.zupan@ijs.si) (c) Date: June, 19973. Past Usage: The hierarchical decision model, from which this dataset is derived, was first presented in M. Bohanec and V. Rajkovic: Knowledge acquisition and explanation for multi-attribute decision making. In 8th Intl Workshop on Expert Systems and their Applications, Avignon, France. pages 59-78, 1988. Within machine-learning, ...
Using Decision Trees for Regression Problems [Case Study]
Introduction : The goal of the blogpost is to equip beginners with the basics of Decision Tree Regressor algorithm and quickly help them to build their first model. We will mainly focus on the modelling side of it. The data cleaning and preprocessing parts would be covered in detail in an upcoming post. In statistics, the mean squared error (MSE) or mean squared deviation (MSD) of an estimator (of a procedure for estimating an unobserved quantity) measures the average of the squares of the errors—that is, the average squared difference between the estimated values and what is estimated. The MSE is a measure of the quality of an estimator—it is always non-negative, and values closer to zero are better. The Mean Squared Error is given by: Enough of theory , let’s start with implementation. P...
Decision Tree model for prediction of Car quality [Case Study]
Problem Statement : To build a Decision Tree model for prediction of car quality given other attributes about the car. Data details: ========================================== 1. Title: Car Evaluation Database ========================================== The dataset is available at “http://archive.ics.uci.edu/ml/datasets/Car+Evaluation” 2. Sources: (a) Creator: Marko Bohanec (b) Donors: Marko Bohanec (marko.bohanec@ijs.si) Blaz Zupan (blaz.zupan@ijs.si) (c) Date: June, 1997 3. Past Usage: The hierarchical decision model, from which this dataset is derived, was first presented in M. Bohanec and V. Rajkovic: Knowledge acquisition and explanation for multi-attribute decision making. In 8th Intl Workshop on Expert Systems and their Applications, Avignon, France. pages 59-78, 1988. With...
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