Research is mainly focus to predict and identify the Terrorist or Perpetrator, To do this, we use an existing data set and apply different Classification Techniques to analyze and interpret the factors that affect our model. For this we use Decision Tree, regression model and Random forest classification.
Our problem is to predict the chance a person can be a Terrorist. We used Classification and Clustering to predict the chances. Attributes used : Marital Status Educational Military , Madras training , Mental Illness Islam , Sex , Age
data.world/sjhaveri publicsafety/terror-attacks-list
Data cleaning: remove unnecessary Attribute Such as Number of people Killed ,Status of Case, source
Data integration : merge the data file from tommy Blanchard and data.word and change attribute name to make it work.
Data transformation : Transform the data by merging the column such as First and last name, Home and nationality etc.
User Inputs : Military , Age, Madrasa Training, Mental Innless ,Educational, Gender, Islam
Plot between the Records of the Dataset and the predicted Probability by the model(naïve bayer)
