Sample4.pdf - Using Big Data Analytics To Predict Crime Type Abstract With the development of the information technology and the computer science big

Sample4.pdf - Using Big Data Analytics To Predict Crime...

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1 Using Big Data Analytics To Predict Crime Type Abstract With the development of the information technology and the computer science, big data is widely used in prediction analytics. Nowadays Crime prediction plays an important role in improving public security and reducing the financial loss of crimes. Studies of crime type predictions, combined with the current police-focused predictions of crime time and place, can make crime predictions more effective. In this paper, we use the crime data of Los Angeles in the last seven years to study the crime type prediction using k means and logistic regression algorithms respectively. 5-fold cross-validation is used to get a reliable and stable model. The results show that both algorithms can be used to predict the type of crime, and logistic regression algorithm is superior to k means algorithm. At last, combined with examples of real word, we analyze the impact of our results. 1. Introduction 1.1. Background introduction With the development of the information technology and the computer science, big data is widely used in prediction analytics. Since the data generation regarding crime is also increased nowadays. Crime prediction is no longer strange for us. Crime prediction plays an important role in improving public security and reducing the financial loss of crimes. The figure 1 is a real crime prediction case in U.S. One commonly used approach in predictive policing seeks to forecast where and when crime will happen; another focuses on who will commit crime or become a victim. Fig. 1 A real crime prediction case 1.2. Why this topic Firstly, it is close to life. Crime is around us and impacts on our lives. As the background introduction introduced, crime prediction has already been effective. Secondly, it is interesting and cool. Only the cool person (e.g. FBI) could predict the crime, which has a really sense of justice. Meanwhile we want to know whether we can predict crime type with what we have learnt and different algorithms’ performance. Research on what impacts the prediction of crime type may have in the real world is one thing we are very curious about. 2. Hypothesis 2.1. Inquiry question
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2 Based on the interesting crime topic, the main idea of the hypothesis in the case study which is “Can the big data predict crime type?” This is precise topic found and can be tested in the real world related to crime information. 2.2. Scope Crime is the general topic which cannot be tested or measured easily. Then narrowing the topic should be needed in first step of defining the hypothesis. If the crime information related to the whole world, it will be too big and not accurate from the result. Because there are different crime rates in different countries especially it may be higher in poor countries. Therefore, the dataset of one city should be the suitable scope to do the case study.
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  • Fall '16
  • cheng

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