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Machine Learning is a subfield of computer science that draws on elements from algorithmic analysis, computational statistics, mathematics, optimization, etc. It is mainly concerned with the use of data to construct models that have high predictive/forecasting ability. Topics include modeling building, applications, theory, etc.

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Interpreting Learning Curves

Bias and variance and their effect on overfitting and underfitting summarized in one illustration Therefore, I think you a fit model, with reasonable variance and bias.
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Model Architecture Design

Indeed you can have two different model architectures and they yield the similar output but that does not generalize on all the data input. For example SVM with linear kernel and logistic regression …
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2 answers
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Binary Classification with Imbalanced Target [closed]

I have a dataset and my objective is to run a Binary Classification, but my target feature, that is supposed to have "True" and "False", only has "True", as a value. I was wondering, is this kind of d …
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1 vote

unsupervised anomaly detection on sparse data

1- You better start with Isolation forest Isolation Forest This is a very simple algorithm where you can control the contamination rate of your data. 2- For visualization you can plot the anomalous po …
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