Archive | Probability

A Gentle Introduction to Probability Distributions

A Gentle Introduction to Probability Distributions

Probability can be used for more than calculating the likelihood of one event; it can summarize the likelihood of all possible outcomes. A thing of interest in probability is called a random variable, and the relationship between each possible outcome for a random variable and their probabilities is called a probability distribution. Probability distributions are […]

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What Is Probability?

What Is Probability?

Uncertainty involves making decisions with incomplete information, and this is the way we generally operate in the world. Handling uncertainty is typically described using everyday words like chance, luck, and risk. Probability is a field of mathematics that gives us the language and tools to quantify the uncertainty of events and reason in a principled […]

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A Gentle Introduction to Uncertainty in Machine Learning

A Gentle Introduction to Uncertainty in Machine Learning

Applied machine learning requires managing uncertainty. There are many sources of uncertainty in a machine learning project, including variance in the specific data values, the sample of data collected from the domain, and in the imperfect nature of any models developed from such data. Managing the uncertainty that is inherent in machine learning for predictive […]

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Resources for Getting Started With Probability in Machine Learning

Resources for Getting Started With Probability in Machine Learning

Machine Learning is a field of computer science concerned with developing systems that can learn from data. Like statistics and linear algebra, probability is another foundational field that supports machine learning. Probability is a field of mathematics concerned with quantifying uncertainty. Many aspects of machine learning are uncertain, including, most critically, observations from the problem […]

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A Gentle Introduction to Probability Scoring Methods in Python

A Gentle Introduction to Probability Scoring Methods in Python

How to Score Probability Predictions in Python and Develop an Intuition for Different Metrics. Predicting probabilities instead of class labels for a classification problem can provide additional nuance and uncertainty for the predictions. The added nuance allows more sophisticated metrics to be used to interpret and evaluate the predicted probabilities. In general, methods for the […]

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Calibrated and Uncalibrated SVM Reliability Diagram

How and When to Use a Calibrated Classification Model with scikit-learn

Instead of predicting class values directly for a classification problem, it can be convenient to predict the probability of an observation belonging to each possible class. Predicting probabilities allows some flexibility including deciding how to interpret the probabilities, presenting predictions with uncertainty, and providing more nuanced ways to evaluate the skill of the model. Predicted […]

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Line Plot of ROC Curve

How and When to Use ROC Curves and Precision-Recall Curves for Classification in Python

It can be more flexible to predict probabilities of an observation belonging to each class in a classification problem rather than predicting classes directly. This flexibility comes from the way that probabilities may be interpreted using different thresholds that allow the operator of the model to trade-off concerns in the errors made by the model, […]

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