Based on the components of the filename, this topic likely involves using a machine learning model—a robust algorithm for classification and regression—trained on a dataset of 100,000 (100K) samples related to Facebook (likely social media metrics, user behavior, or advertising data).
: Many datasets labeled "100K" are used to train classifiers (like RF) to detect spam or misinformation on Facebook. Key Source : Detecting Fake News on Social Media (ACM) . 4. Technical Specification: Random Forest (RF) 100K RF FACEBOOK.xlsx
: Random Forest is preferred for 100K-row datasets because it handles high-dimensional data (many columns in an .xlsx) without the extensive preprocessing required by deep learning. Based on the components of the filename, this
: Predicting personality or "Likes" using ensemble methods. 100K RF FACEBOOK.xlsx