Remove 2017 Remove Data mining Remove Measurement Remove Metrics
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Magnificent Mobile Website And App Analytics: Reports, Metrics, How-to!

Occam's Razor

But why blame others, in this post let's focus on one important reason whose responsibility can be squarely put on your shoulders and mine: Measurement. Create a distinct mobile website and mobile app measurement strategies. Mobile content consumption, behavior along key metrics (time, bounces etc.)

Metrics 141
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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

the weight given to Likes in our video recommendation algorithm) while $Y$ is a vector of outcome measures such as different metrics of user experience (e.g., Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well.

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Make Your Investment in Analytic Technology Pay Off With Decision Requirements Modeling

Decision Management Solutions

Like many enterprises, you’ve likely made a hefty investment in analytic technology—from interactive dashboards and advanced visualization tools to data mining, predictive analytics, machine learning (ML), and artificial intelligence (AI). 1 MIT Sloan Management Review September 06, 2017. We can show you how to accomplish this.

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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

Working with highly imbalanced data can be problematic in several aspects: Distorted performance metrics — In a highly imbalanced dataset, say a binary dataset with a class ratio of 98:2, an algorithm that always predicts the majority class and completely ignores the minority class will still be 98% correct. return synthetic.

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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature. Conference on Knowledge Discovery and Data Mining, pp.

Modeling 139
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Top 10 Analytics And Business Intelligence Trends For 2020

datapine

While we work on programs to avoid such inconvenience , AI and machine learning are revolutionizing the way we interact with our analytics and data management while increment in security measures must be taken into account. It’s an extension of data mining which refers only to past data.

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What Is Data Intelligence?

Alation

Data catalogs then integrate compliance at the point of consumption, so people are alerted to sensitive data where it lives. Source: “What’s Your Data Strategy?” HBR Review May/June 2017. Data Intelligence and Metadata. Data intelligence is fueled by metadata. Implement Data Intelligence Software.