Sun Nov 23 08:45:00 UTC 2025: Here’s a summary of the text, followed by a rewritten version as a news article:

Summary:

  • The provided text is from the November 23, 2025 e-paper of The Hindu.
  • It includes a brief explanation of Random Forest, a machine learning technique that uses multiple decision trees to make predictions. Random forests are more accurate and less prone to overfitting than single decision trees.
  • The article cites a study published in PNAS on November 17, where scientists used random forest models to analyze the chemical fingerprints of fossils, leading to the discovery of potential evidence of photosynthetic microbes from 2.5 billion years ago.

News Article:

Random Forest Machine Learning Reveals Ancient Photosynthetic Life, Indian Researchers Report

New Delhi, November 23, 2025 – An article published today in The Hindu highlights the power of random forest, a machine learning technique, in uncovering new scientific insights. The feature discusses the technique’s growing applications.

Random Forest uses multiple decision trees to derive at a conclusion.

The Hindu article cites a recent study published in the journal PNAS on November 17. In the study, scientists employed random forest models to analyze the chemical composition of fossils. By training the models to recognize chemical “fingerprints,” the researchers were able to distinguish between organic molecules originating from living organisms and those from natural processes. The results suggest the presence of photosynthetic microbes dating back 2.5 billion years.

“The Random Forest method minimises this issue by building a large number of trees, each trained on a slightly different random sample of the data,” the article explains.

This breakthrough underscores the potential of artificial intelligence and machine learning in paleontology and other scientific fields.

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