Find hidden patterns in existing data, public repositories combined with your R&D data using statistical, machine learning models.
Based on a training dataset, an algorithm learns to identify patterns in the data and can make a number of predictions, for which it can be “rewarded” or “punished”. After numerous iterations, the mature algorithms can be applied to real-world data.
These underlying algorithms can take various forms, including decision trees, naïve Bayes classification, logistic regression, support vector machines, clustering algorithms, principal component analysis and many more.
