Blogs tagged Python Machine Learning Client for SAP HANA

In time series, an outlier is a data point that is different from the general behavior of remaining data points. In Predictive Analysis Library (PAL) of SAP HANA, we have automatic outlier detection for time series. You can find more details in... Read More »

The recent success of applying state-of-the-art AI algorithms on tasks with modern big data has raised concerns on their efficiency. For instance, ensemble methods like random forest usually require lots of sub-learners to achieve favorable... Read More »

Gradient Boosting is an ensemble machine learning algorithms, it is used to build predictive models for both regression and classification problems. In gradient boosting, a weak predictive model, typically a decision tree, is trained on the input... Read More »

UPDATE from April 2023: Thanks to everyone, who participated in this challenge. While it is no longer possible to receive a badge for completing this challenge, its content is still available along with solutions for everyone interested in... Read More »

Picture this – you are the manager of a supermarket and would like to forecast the sales in the next few weeks and have been provided with the historical daily sales data of hundreds of products. What kind of problem would you classify this as? Of... Read More »

Machine learning models, e.g. classification and regression model, contain the relationships and patterns between features in the training dataset which could be applied to similar data in the future for prediction. Model training could be time... Read More »

In a few related blog posts[1][2], we have shown the analysis of time-series using traditional approaches like seasonal decomposition, ARIMA and exponential smoothing. However, those traditional approaches have some drawbacks for time-series... Read More »

In this blog post, we will show users how to perform time-series modeling and analysis using SAP HANA Predictive Analysis Library(PAL). Different from the original SQL interface, here we call PAL procedures through the Python machine learning client... Read More »

In a few separate blog posts, we have discussed the problem of anomaly detection in dataset with multiple features using techniques like one-class classification, clustering(DBSCAN) as well as statistical tests. However, all the aforementioned... Read More »

We have introduced several methods for outlier detection in a few separate blog posts, inclusive of outlier detection using statistical tests and clustering. Typically, these methods can only detect outliers the input dataset, and the detection... Read More »