SGD and Logistic Regression #5
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…generic plot, added an argument to specify what evaluation metrics need to be displayed/plotted, ,tests WIP
… to a callable metric (accuracy, mse, etc.)
…tch_size. Created a utils.model.py file where all model-specific utilities live
meghgala
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commit a6f019a Author: hasnainroopawalla <hasnain.roopawalla@gmail.com> Date: Fri Nov 12 16:25:48 2021 +0100 Added AdaGrad and RMSProp to the README commit c861c2b Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Fri Nov 12 16:20:14 2021 +0100 Update README.md commit 66e943c Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Fri Nov 12 16:10:53 2021 +0100 Added the AdaGrad and RMSProp Optimizer (hasnainroopawalla#7) * Added the AdaGrad and RMSProp Optimzer * Fixed linting * Fixed edge case in SGD commit 8e393dd Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Wed Nov 10 16:30:32 2021 +0100 SGD and Logistic Regression (hasnainroopawalla#5) * Added logistic regression and refactored loss function arguments * Working logistic regression with BCEP loss, converted all plots to a generic plot, added an argument to specify what evaluation metrics need to be displayed/plotted, ,tests WIP * Updated evaluation metric input, added a metric_map to map the string to a callable metric (accuracy, mse, etc.) * Better log loss method and added assertions for X_train and y_train data types * Added random weight initialization and handling of zero division in BCE objective * Removed dependency of metric_map for string-to-method conversion * Converted model.history to defaultdict * Moved plot_metrics to plots.py * Updated version number * Updated release.sh * Added all optimizers and loss function classes to their respective __init__.py files * Removed plot flag from model.fit - WIP * Updated README.md * Fixed linting for __init__.py * Added a generate_minibatch method to generate batches based on the batch_size. Created a utils.model.py file where all model-specific utilities live * Reorganized tests * Test CI mypy * Updated requirements.txt and the CI * Replaced np.float64 with float and fixed mypy errors, added a mypy.ini config file * Update README.md * Update README.md * Update requirements.txt * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Added momentum to SGD * Added a Dataset class which includes validation of X and y. Refactored regression examples to reflect these changes * Moved examples/ to ShowML/ * Added a model.compile method * Reorganized files and created a data_loader.py file * Version number update * Added mypy installation to CI * Added pytest installation to CI
meghgala
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Nov 16, 2021
commit a6f019a Author: hasnainroopawalla <hasnain.roopawalla@gmail.com> Date: Fri Nov 12 16:25:48 2021 +0100 Added AdaGrad and RMSProp to the README commit c861c2b Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Fri Nov 12 16:20:14 2021 +0100 Update README.md commit 66e943c Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Fri Nov 12 16:10:53 2021 +0100 Added the AdaGrad and RMSProp Optimizer (hasnainroopawalla#7) * Added the AdaGrad and RMSProp Optimzer * Fixed linting * Fixed edge case in SGD commit 8e393dd Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Wed Nov 10 16:30:32 2021 +0100 SGD and Logistic Regression (hasnainroopawalla#5) * Added logistic regression and refactored loss function arguments * Working logistic regression with BCEP loss, converted all plots to a generic plot, added an argument to specify what evaluation metrics need to be displayed/plotted, ,tests WIP * Updated evaluation metric input, added a metric_map to map the string to a callable metric (accuracy, mse, etc.) * Better log loss method and added assertions for X_train and y_train data types * Added random weight initialization and handling of zero division in BCE objective * Removed dependency of metric_map for string-to-method conversion * Converted model.history to defaultdict * Moved plot_metrics to plots.py * Updated version number * Updated release.sh * Added all optimizers and loss function classes to their respective __init__.py files * Removed plot flag from model.fit - WIP * Updated README.md * Fixed linting for __init__.py * Added a generate_minibatch method to generate batches based on the batch_size. Created a utils.model.py file where all model-specific utilities live * Reorganized tests * Test CI mypy * Updated requirements.txt and the CI * Replaced np.float64 with float and fixed mypy errors, added a mypy.ini config file * Update README.md * Update README.md * Update requirements.txt * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Added momentum to SGD * Added a Dataset class which includes validation of X and y. Refactored regression examples to reflect these changes * Moved examples/ to ShowML/ * Added a model.compile method * Reorganized files and created a data_loader.py file * Version number update * Added mypy installation to CI * Added pytest installation to CI
hasnainroopawalla
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Nov 16, 2021
* Added logistic regression and refactored loss function arguments * Working logistic regression with BCEP loss, converted all plots to a generic plot, added an argument to specify what evaluation metrics need to be displayed/plotted, ,tests WIP * Updated evaluation metric input, added a metric_map to map the string to a callable metric (accuracy, mse, etc.) * Better log loss method and added assertions for X_train and y_train data types * Added random weight initialization and handling of zero division in BCE objective * Removed dependency of metric_map for string-to-method conversion * Converted model.history to defaultdict * Moved plot_metrics to plots.py * Updated version number * Updated release.sh * Added all optimizers and loss function classes to their respective __init__.py files * Removed plot flag from model.fit - WIP * Updated README.md * Fixed linting for __init__.py * Added a generate_minibatch method to generate batches based on the batch_size. Created a utils.model.py file where all model-specific utilities live * Reorganized tests * Added pytest to requirements.txt and removed unused import in test_metrics.py * Test CI mypy * Updated requirements.txt and the CI * Replaced np.float64 with float and fixed mypy errors, added a mypy.ini config file * Update README.md * Update README.md * Update requirements.txt * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Added momentum to SGD * Added a Dataset class which includes validation of X and y. Refactored regression examples to reflect these changes * Moved examples/ to ShowML/ * Create test_dataset.py * Squashed commit of the following: commit a6f019a Author: hasnainroopawalla <hasnain.roopawalla@gmail.com> Date: Fri Nov 12 16:25:48 2021 +0100 Added AdaGrad and RMSProp to the README commit c861c2b Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Fri Nov 12 16:20:14 2021 +0100 Update README.md commit 66e943c Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Fri Nov 12 16:10:53 2021 +0100 Added the AdaGrad and RMSProp Optimizer (#7) * Added the AdaGrad and RMSProp Optimzer * Fixed linting * Fixed edge case in SGD commit 8e393dd Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Wed Nov 10 16:30:32 2021 +0100 SGD and Logistic Regression (#5) * Added logistic regression and refactored loss function arguments * Working logistic regression with BCEP loss, converted all plots to a generic plot, added an argument to specify what evaluation metrics need to be displayed/plotted, ,tests WIP * Updated evaluation metric input, added a metric_map to map the string to a callable metric (accuracy, mse, etc.) * Better log loss method and added assertions for X_train and y_train data types * Added random weight initialization and handling of zero division in BCE objective * Removed dependency of metric_map for string-to-method conversion * Converted model.history to defaultdict * Moved plot_metrics to plots.py * Updated version number * Updated release.sh * Added all optimizers and loss function classes to their respective __init__.py files * Removed plot flag from model.fit - WIP * Updated README.md * Fixed linting for __init__.py * Added a generate_minibatch method to generate batches based on the batch_size. Created a utils.model.py file where all model-specific utilities live * Reorganized tests * Test CI mypy * Updated requirements.txt and the CI * Replaced np.float64 with float and fixed mypy errors, added a mypy.ini config file * Update README.md * Update README.md * Update requirements.txt * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Added momentum to SGD * Added a Dataset class which includes validation of X and y. Refactored regression examples to reflect these changes * Moved examples/ to ShowML/ * Added a model.compile method * Reorganized files and created a data_loader.py file * Version number update * Added mypy installation to CI * Added pytest installation to CI * dataset tests completed * Squashed commit of the following: commit a6f019a Author: hasnainroopawalla <hasnain.roopawalla@gmail.com> Date: Fri Nov 12 16:25:48 2021 +0100 Added AdaGrad and RMSProp to the README commit c861c2b Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Fri Nov 12 16:20:14 2021 +0100 Update README.md commit 66e943c Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Fri Nov 12 16:10:53 2021 +0100 Added the AdaGrad and RMSProp Optimizer (#7) * Added the AdaGrad and RMSProp Optimzer * Fixed linting * Fixed edge case in SGD commit 8e393dd Author: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com> Date: Wed Nov 10 16:30:32 2021 +0100 SGD and Logistic Regression (#5) * Added logistic regression and refactored loss function arguments * Working logistic regression with BCEP loss, converted all plots to a generic plot, added an argument to specify what evaluation metrics need to be displayed/plotted, ,tests WIP * Updated evaluation metric input, added a metric_map to map the string to a callable metric (accuracy, mse, etc.) * Better log loss method and added assertions for X_train and y_train data types * Added random weight initialization and handling of zero division in BCE objective * Removed dependency of metric_map for string-to-method conversion * Converted model.history to defaultdict * Moved plot_metrics to plots.py * Updated version number * Updated release.sh * Added all optimizers and loss function classes to their respective __init__.py files * Removed plot flag from model.fit - WIP * Updated README.md * Fixed linting for __init__.py * Added a generate_minibatch method to generate batches based on the batch_size. Created a utils.model.py file where all model-specific utilities live * Reorganized tests * Test CI mypy * Updated requirements.txt and the CI * Replaced np.float64 with float and fixed mypy errors, added a mypy.ini config file * Update README.md * Update README.md * Update requirements.txt * Update README.md * Update README.md * Update README.md * Update README.md * Update README.md * Added momentum to SGD * Added a Dataset class which includes validation of X and y. Refactored regression examples to reflect these changes * Moved examples/ to ShowML/ * Added a model.compile method * Reorganized files and created a data_loader.py file * Version number update * Added mypy installation to CI * Added pytest installation to CI * Delete model.py * Update python_packaging.yml Co-authored-by: hasnainroopawalla <hasnain.roopawalla@gmail.com> Co-authored-by: Hasnain Roopawalla <37022937+hasnainroopawalla@users.noreply.github.com>
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Datasetclass to initialize the input to the model