Classification predictive modeling typically involves predicting a class label. Nevertheless, many machine learning algorithms are capable of predicting a probability…

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## A Gentle Introduction to the Bayes Optimal Classifier

The Bayes Optimal Classifier is a probabilistic model that makes the most probable prediction for a new example. It is…

Continue Reading## 6 Key Concepts in Andrew Ng’s “Machine Learning Yearning”

For tasks that humans are good at, you can compare your system’s performance to those of humans, which gives you…

Continue Reading## Finding the optimal dating strategy for 2019 with probability theory

It’s 1/N. And as n gets larger the larger timeframe we consider, this probability will tend to zero. Alright, you…

Continue Reading## [ Archived Post ] Reinforcement Learning: A Survey

→ the agent should take into account the future as well → the reward overtime → , however, when the timestamp…

Continue Reading## The Digital Fertilizer Challenge

It would become fertilizer for algae, which would take over the tank, and the fish would die. ” My kids…

Continue Reading## 10 Tips for Choosing the Optimal Number of Clusters

The cValid package can be used to simultaneously compare multiple clustering algorithms, to identify the best clustering approach and the…

Continue Reading## Probability theory and the optimal dating strategy for 2018

It’s 1/N. And as n gets larger the larger timeframe we consider, this probability will tend to zero. Alright, you…

Continue Reading## Spectral graph clustering and optimal number of clusters estimation

Next, we will provide an implementation for the eigengap heuristic computing of the optimal number of clusters in a dataset…

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