• Dr. T. Amalraj Victorie
• M. Vasuki
• M.Moniksha

With the widespread proliferation of blogs, there arises a crucial necessity to extract pertinent information for addressing a spectrum of issues spanning social, political, criminal, and other domains. It can extracting meaningful information from blogs is crucial . The goal of blogs is to classify the bloggers based on their writing style, content , or other features. It can be analysis the data from the Random Forest algorithms to classify bloggers whether they are professional or otherwise from the Kozhikode and Boyer Ahmad province in Iran. In this algorithm , it can analysis the data through the tree-based ensemble learning technique in machine learning .In this algorithm, it can be process through the ensemble learning methodology that analysis the data for predictions of these tree ,it can predicts accuracy value. As a means of comparison, this paper suggests employing the Random Forest algorithm for categorizing blogs, utilizing the identical dataset . The findings indicated that employing ensemble classification using the Random Forest algorithm resulted in greater accuracy compared to previous research utilizing the same algorithm.

: Random forest , decision tree process , ensemble learning method, blog poster prediction, Python 3.6, Machine Learning, Data Analysis, Training Data ,Testing Data

"DESIGNING A WEB BLOG POSTER UTILIZING RANDOM FOREST ALGORITHM AND DECISION TREES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.f212-f221, May-2024, Available :http://www.jetir.org/papers/JETIR2405523.pdf

"DESIGNING A WEB BLOG POSTER UTILIZING RANDOM FOREST ALGORITHM AND DECISION TREES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppf212-f221, May-2024, Available at : http://www.jetir.org/papers/JETIR2405523.pdf