Machine-Learning
The purpose of this work is to predict the success of a terrorist attack using approaches in machine learning. The research was carried out on the Global Terrorism Database (GTD), an open database which contains a list of terrorist activities. Eight machine learning algorithms have been applied on some selected set of features from the data set to achieve an maximum accuracy of 93%.
The algorithms implemented are :
1. Random Forest
2. K-Nearest Neighbors Algorithm
3. Linear Regression
4. Linear Discriminant Analysis
5. Decision Tree Classifier
6. Naive Bayes
7. Support Vector Classifier
8. Logistic Regression
Out of all the above mentioned algorithms Random forest proves to be the most effecient.