Source of Arthur Samuel's definition of machine learning
14 Many people seem to agree that Arthur Samuel wrote or said in 1959 that machine learning is the " Field of study that gives computers the ability to learn without being explicitly programmed ". For …
What are bias and variance in machine learning?
Aug 12, 2020 · Ensembles of Machine Learning models can significantly reduce the variance in your predictions. The Bias-Variance tradeoff If your model is underfitting, you have a bias problem, and …
machine learning - What is Ground Truth - Data Science Stack Exchange
In machine learning, the term "ground truth" refers to the accuracy of the training set's classification for supervised learning techniques. This is used in statistical models to prove or disprove research …
What does Logits in machine learning mean?
Apr 30, 2018 · "One common mistake that I would make is adding a non-linearity to my logits output." What does the term "logit" means here or what does it represent ?
machine learning - What's The Difference Between The Terms Predictor ...
Predictor Variable: One or more variables that are used to determine or predict the target variable. Whereas Wikipedia contains the following definition of the word 'feature': Feature is an individual …
machine learning - What is the exact definition of VC dimension?
I'm studying machine learning from Andrew Ng Stanford lectures and just came across the theory of VC dimensions. According to the lectures and what I understood, the definition of VC dimension can be …
machine learning - 'Feature' definition - Data Science Stack Exchange
Jul 12, 2019 · Feature in the data science context is the name of your variable, answering your question it would be things like name, address, price, volume, etc. It is also known as attributes, columns, …
Definition of a model in machine learning - Data Science Stack Exchange
Jul 21, 2016 · In machine learning, the model is the center of gravity, everything revolves around it. Yet, people have different definitions of 'model'; but in my opinion, the best definition of model in ML is …
machine learning - Definition of Type 1 and Type 2 Errors in ...
May 27, 2019 · Why are the type 1 and type 2 errors as defined in bankruptcy prediction, different from type 1 and type 2 errors based on confusion matrix? In bankruptcy literature: Type 1 error: predicting a
machine learning - Generalization Error Definition - Data Science Stack ...
machine-learning deep-learning pac-learning Improve this question edited Jul 11, 2018 at 10:40 Stephen Rauch ♦