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How To Plot A Decision Boundary For Machine Learning Algorithms in Python

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Manage episode 365712452 series 3474670
Contenuto fornito da HackerNoon. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da HackerNoon o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/how-to-plot-a-decision-boundary-for-machine-learning-algorithms-in-python-3o1n3w07.
Classification algorithms learn how to assign class labels to examples (observations or data points), although their decisions can appear opaque.
Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-science, #machine-learning, #python3, #python-programming, #python, #python-top-story, #python-tutorials, #python-developers, #hackernoon-es, and more.
This story was written by: @kvssetty. Learn more about this writer by checking @kvssetty's about page, and for more stories, please visit hackernoon.com.
How To Plot A Decision Boundary For Machine Learning Algorithms in Python is a popular diagnostic for understanding the decisions made by a classification algorithm is the decision surface. This is a plot that shows how a trained machine learning algorithm predicts a coarse grid across the input feature space. A decision surface plot is a powerful tool for understanding how a given model ‘sees’ the prediction task and how it has decided to divide up the feature space by class label. The complete source code is available at my git repository.

  continue reading

153 episodi

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iconCondividi
 
Manage episode 365712452 series 3474670
Contenuto fornito da HackerNoon. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da HackerNoon o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

This story was originally published on HackerNoon at: https://hackernoon.com/how-to-plot-a-decision-boundary-for-machine-learning-algorithms-in-python-3o1n3w07.
Classification algorithms learn how to assign class labels to examples (observations or data points), although their decisions can appear opaque.
Check more stories related to data-science at: https://hackernoon.com/c/data-science. You can also check exclusive content about #data-science, #machine-learning, #python3, #python-programming, #python, #python-top-story, #python-tutorials, #python-developers, #hackernoon-es, and more.
This story was written by: @kvssetty. Learn more about this writer by checking @kvssetty's about page, and for more stories, please visit hackernoon.com.
How To Plot A Decision Boundary For Machine Learning Algorithms in Python is a popular diagnostic for understanding the decisions made by a classification algorithm is the decision surface. This is a plot that shows how a trained machine learning algorithm predicts a coarse grid across the input feature space. A decision surface plot is a powerful tool for understanding how a given model ‘sees’ the prediction task and how it has decided to divide up the feature space by class label. The complete source code is available at my git repository.

  continue reading

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