Countries Condition of Forestation and Trees Percentage using Machine learning | IEEE Conference Publication | IEEE Xplore

Countries Condition of Forestation and Trees Percentage using Machine learning


Abstract:

Most countries are now in a dangerous place for forestation and some are in developed forestation. So forestation and trees percentage prediction are to predict the condi...Show More

Abstract:

Most countries are now in a dangerous place for forestation and some are in developed forestation. So forestation and trees percentage prediction are to predict the condition of the countries about their condition of forestation and tress percentage. The paper is about a machine learning model to predict the countries condition. We used logistic regression, SVM AND Naive Bayes to predict the condition also for matrix. we also find the accuracy of logistic regression, SVM, Nave Bayes, Ada boosting classifier, Decision tree, ANN, Linear Discriminant Analysis, Gradient Boosting Classifier, MLP Classifier to find our best accuracy and compare with them with our data. we give details of selected algorithms. We collected some previous data and present data and comparing them to predict the condition of the country. we use some conditions and logic for machine learning. By logistic regression, SVM and Nave Bayes will show us the prediction and condition of those chosen countries.
Date of Conference: 22-23 November 2019
Date Added to IEEE Xplore: 16 June 2020
ISBN Information:
Conference Location: Moradabad, India

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