They represent errors in the measurement, bad data collection(not careful while data collection), or simply show those variables that are not considered while collecting the data.
statistics are affected by the outliers - Mean - Standard deviation - Median - Inter-Quartile Range (IQR) @AnalyticsVidhya analyticsvidhya.com/blog/2021/05/w…
Outlier detection and removal is a crucial data analysis step for a machine learning model, as outliers can significantly impact the accuracy of a model if they are not handled properly Blog Link - @AnalyticsVidhya analyticsvidhya.com/blog/2021/05/f…
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✅Drop an outlier if - - know that it’s completely wrong - You have a lot of data in hand - You have an option to going back ✅Don’t drop an outlier if - - Your results are critical
✅Most popular outlier detection methods in #MachineLearning🥳 -Z-Score -IQR (Interquartile Range) -Mahalanobis Distance -DBSCAN (Density-Based Spatial Clustering of Applications with Noise -Local Outlier Factor (LOF) -One-Class SVM (Support Vector Machine)
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