Decision trees are among the more popular applications of machine learning in the capital markets. Uses include finding patterns in request-for-quote (RFQ) datasets and predicting stock prices.
For example, you might want to predict the sex of a person (male or female) based on their age, state where they live, income and political leaning. There are many other techniques for binary ...
Development and Validation of a Machine Learning Approach Leveraging Real-World Clinical Narratives as a Predictor of Survival in Advanced Cancer Administering systemic anticancer treatment (SACT) to ...
Low-dose computed tomography (LDCT) screening is effective in reducing lung cancer mortality by detecting the disease at earlier, more treatable stages. However, high false-positive rates and the ...
Executives are inviting geographers into the boardroom. Why? Together, they are answering some of the most complex climate-risk questions: · Where are the greatest threats to buildings and other ...
Dr. James McCaffrey of Microsoft Research says decision trees are useful for relatively small datasets and when the trained model must be easily interpretable, but often don't work well with large ...
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