There are relatively few works dealing with conformal prediction for multi-task learning issues, and this is particularly true multi-target regression. This paper focuses on the problem of providing valid (i.e., frequency calibrated) multi-variate predictions. To do so, we propose to use copula functions inductive prediction, illustrate our proposal by applying it deep neural networks random fo...

House price fluctuates each and every year due to changes in land value change infrastructure around the area. Centralised system should be available for prediction of house correlation with neighbourhood infrastructure, will help customer estimate house. Also, it assists come a conclusion where buy when purchase Different factors are taken into consideration while predicting worth like locatio...

Abstract: 
 Recently, there have been studies on the use of machine learning algorithms for price prediction in many different areas such as stock market, rent a house and used car sales. Studies give information about which algorithm is more successful using methods. The most commonly method linear regression model. In our study, we examined effectiveness model prediction. applied data se...

Artificial Intelligence (AI) is the human-like intelligence imbued in machines so that they can perform tasks normally require human intelligence. Machine learning an AI technique which carries on concepts of predictive analytics with one important distinction: system make assumptions, test hypotheses, and learn independently. XGBoost, Extreme gradient boosting, a popular machine-learning libra...