2015 Apr Opinions, Interviews, Reports

All (12) | News, Features (2) | Opinions, Interviews, Reports (4) | Publications (2) | Software (4)

The Myth of Model Interpretability

Deep networks are widely regarded as black boxes. But are they truly uninterpretable in any way that logistic regression is not?

on Apr 27, 2015 in Deep Learning, Deep Neural Network, Interpretability, Support Vector Machines, Zachary Lipton
New Hybrid Rare-Event Sampling Technique for Fraud Detection

Proposed hybrid sampling methodology may prove useful when building and validating machine learning models for applications where target event is rare, such as fraud detection.

on Apr 26, 2015 in Bootstrap sampling, Fraud Detection, Sampling
Data Science 101: Preventing Overfitting in Neural Networks

Overfitting is a major problem for Predictive Analytics and especially for Neural Networks. Here is an overview of key methods to avoid overfitting, including regularization (L2 and L1), Max norm constraints and Dropout.

on Apr 17, 2015 in Neural Networks, Nikhil Buduma, Overfitting, Regularization
Interview: Ksenija Draskovic, Verizon on Dissecting the Anatomy of Predictive Analytics Projects

We discuss Predictive Analytics use cases at Verizon Wireless, advantages of a unified data view, model selection and common causes of failure.

on Apr 15, 2015 in Customer Intelligence, Interview, Ksenija Draskovic, Optimization, Predictive Analytics, Project Fail, Use Cases, Verizon

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