Women Safety Prediction using Logistic Regression Model
V. Sushma Swaraj1, L. Bhavya2, G. Pooja3, R. Deva Revathi4

1V. Sushma Swaraj, Student, Dept of CSE, JNTUACEP, Pulivendula – 516390, YSR (Dist), A.P.
2L. Bhavya, Asst. Professor (Adhoc), Dept of CSE, JNTUACEP, Pulivendula, YSR (Dist), A.P.
3G. Pooja , Student, Dept of CSE, JNTUACEP, Pulivendula – 516390, YSR (Dist), A.P.
4R. DevaRevathi , Student, Dept of CSE, JNTUACEP, Pulivendula – 516390, YSR (Dist), A.P.
Manuscript received on February 27, 2020. | Revised Manuscript received on March 14, 2020. | Manuscript published on March 30, 2020. | PP: 5056-5059 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9772038620/2020©BEIESP | DOI: 10.35940/ijrte.F9772.038620

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Safety of Women has become a major issue in India. Especially at night women think a lot before coming out of their homes. We daily come up with news of how women are subjected to a lot of violence and harassment or get molested in public areas. This paper focuses on the issue of helping Women that they don’t ever never feel alone in the middle of any situations. The project idea is to predict whether the given place at any time is safe for a women to go or not. There are many pre-existing applications that are useful at the time of crisis situations. At some situations when a women is in trouble, she is not able to use those applications. And there are also so many rehabilation centres which are used after the situation has happened. But our proposed model will help women to take precautions so that they never ever get that situation. For this idea we used Machine Learning. Machine learning is used to train the data and make quality predictions by recognizing the patterns in data. We applied different algorithms like Naïve Bayes, K-Nearest Neighbours, Logistic Regression models. Logistic regression is the best fit among other machine learning algorithms and it is more effective than others. In this paper, we used Logistic regression algorithm of Sklearn machine learning library to classify the dataset. Information about some set of areas in Tamilnadu are collected and was used in our project. When a women alone want to go out for any personal work or any financial work without knowing any safety details about the place she wants to go our application helps more better.
Keywords: K-Nearest Neighbours, Logistic Regression, Machine Learning, Naïve Bayes, Sklearn, Women safety.
Scope of the Article: Machine Learning.