Isolation Forest

Anomaly / Outliers: in Data Science data patterns that have different characteristics from normal data are called anomalies. By detecting anomalies, it provides critical and actionable information in various application domains such as eCommerce, retail , banking etc. Isolation forest algorithm: Isolation forest is the newest techniques to detect anomalies. The is based on various... Continue Reading →

Channel profitability

Difficulties in withstanding the competition The rise of newer technology has made the sale of goods available across a plethora of modes. Sellers are not restricted by traditional selling platforms to make sales; online selling has grown tremendously over the last few years. With many players testing the scope of online selling, ability to withstand... Continue Reading →

One class SVM

What is it? One-Class SVM is used for unsupervised outlier and novelty detection.  Normal data points to build the model so the algorithm can set a correct boundary for the given samples. Nu, Gamma, and Kernel are parameters for the model these impact the result significantly. So we need to experiment with these parameters until... Continue Reading →

Improve accuracy of sales prediction (Part 1)

Why sales prediction is inaccurate ? Outlier in sales value that is abnormally high or low compared to the values in the sales time series. They can lead to inaccurate forecasts, we have to build a system that can automatically detect outliers and ignore them during forecast calculation. Advantages of outliers analysis Improve data accuracy.... Continue Reading →

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