WIP: Visualize misclassifications #2
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SaumyaSinghal
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Mar 31, 2020
Updating KaairaGupta/master
SaumyaSinghal
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Mar 31, 2020
…ogistic Regression (mozilla#12) * Data Loaded from vehicles.csv * Data visulaization and training model with ifferent algorithms * Evaluation of model is done. * Changed model from Logistic Regression to Support Vector Machine At first attempt i used three differnet models but Logistic Regression , Support Vector Machine and Decision Tree, and the overall accuracy with LR was better than any other but with changing validation parameters in SVM classification , model accuacy increased from 82% to 88%. * Delete train and test model-checkpoint.ipynb * Changed file named. * all python modules were added * docstrings were added * labels added in confusion matrix * Histogram colors were changed into single color * solved histogram issue * Update modules.py * changes made in histogram * Update modules.py * sorted histogram * Update modules.py * labels were added for confusion matrix * Python Custom Modules were added * Update Vehicle_Classifier.ipynb * Update modules.py * Update modules.py * Update modules.py * added labels in confusion matrix * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Requested Changes were made * Update modules.py * change categorical data into numerical data * change areguments in LR model * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Update modules.py * Requested changes were made * Update modules.py * Update modules.py * Update modules.py * Delete Untitled.ipynb * code formatted using python Black * Requested changes were made * shifted classifier's code from modules.py to ModelEvaluation.py * removed learning curves from file * added function for model evaluation in Model Evaluation file * updated svm and lr * added comments * added doc strings * Update ModelEvaluation.py * Update ModelEvaluation.py * Update Vehicle_Classifier.ipynb * Update modules.py * added descriptions * added interpretations of visualization
SaumyaSinghal
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Mar 31, 2020
…nition of classes (mozilla#86) * Contribution to issue #2 * Eliminació de l'arxiu de prova * Eliminació de l'arxiu de prova * Fixed axes when not numbers and removed superfluous function. * Initial commit to Issue mozilla#7 Visualization of missclassifications. * Adding explanatory graphs for the notebook regarding Issue mozilla#7 * Better graph to illustrate option 'hits-fails'.
SaumyaSinghal
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Mar 31, 2020
* Add Logistic Regression Model for Winequality dataset Signed-off-by: SanchiMittal <[email protected]> * Add python modules Signed-off-by: SanchiMittal <[email protected]> * Minor Changes * Add Black Formatting
SaumyaSinghal
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Mar 31, 2020
Fixed #2, train and test a classification model on vehicles dataset
SaumyaSinghal
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Mar 31, 2020
…n the train-test split ratio (mozilla#72) * Contribution to issue #2 * Eliminació de l'arxiu de prova * Eliminació de l'arxiu de prova * Fixed axes when not numbers and removed superfluous function. * Minor changes to modules in file data_exploration.py. Co-authored-by: mlopatka <[email protected]>
SaumyaSinghal
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Mar 31, 2020
SaumyaSinghal
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Mar 31, 2020
these committed changes fixes issue #3 of traversal space of train-test splits using KNN model.in #2 i have used decision tree and further recommended outlier detection algorithm for classification. so in this PR i have used KNN and compared results with previous classfication.this PR uses already defined modules in #2.
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Mar 31, 2020
#3 traversal of train_test_split
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* Create Readme.md * Create files for exploring issue #2 * Format using black * Remove notebook from master * Increase modularization * create file for issue 6 * remove file added by mistake * Create notebook for issue 6 * Re-upload to the right folder * Delete file from the incorrect folder
SaumyaSinghal
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Mar 31, 2020
* Update .gitignore * Preliminary Analysis * Helper modules (Bar and Hist graph) * Rough KNN algorithm implemented * Delete libraries.py * KNN classifier refactored and polished Returns only variable of intests for use the metrics calculations. * refactored for performance just the required functions imported * draft mlp classifier implemented to be reviewed * ... * Threshold conversion logic implemented Since knn.predict calculates a probability, we implement a logic for binary classification * Prelimary cleaning and knn model classification implemented! * Adjusted plor error with title placement * ... * Files reformated with 'Black' * Logistic Regression classifier * Refactores modules to improve modularity * Implemented Log Reg * Deleted mpl module to focus on knn and log reg * Refactors gotignore to my personal folder * refactored for readability * Implementation to add counts and relative percentages on bars graph * Refactored name #2, Completed Prelimary Analysis and Interpreted Results * Update Issue #2 - Train and test a classification model (PRESC).ipynb * Files reformated with 'Black' * Display Error corrected * Interpreted choice of hyper-parameters * Refactored and Added Modules used for Issue 3 * Prelimanry Analysis - Traversal of the space of train_test splits * Issue#3 complete * Removed Issues #2 and #3 ipynb * Issue mozilla#4 - completed Issue mozilla#4 - Traversal of the space of cross-validation folds * Delete defaults_data.csv Removing duplication of the existing data set which can be loaded from the repos root directory. Co-authored-by: mlopatka <[email protected]>
SaumyaSinghal
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Mar 31, 2020
…ozilla#92) * Classification model wine.csv * Classification model wine.csv * Merging modifications
SaumyaSinghal
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Mar 31, 2020
#2 Dropped quality, shifted the logic to python file, shifted imports to the top, added confusion_matrix and classification_report
SaumyaSinghal
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Mar 31, 2020
…el (Stochastic Gradient Descent) on winequality.csv (mozilla#58) * adds incomplete files * adds .ipynb, .py and updates environment.yml * Delete winequality.ipynb removing duplicate files * Delete winequality_modules.py removing duplicate files * Delete winequality.ipynb removing incomplete files * Delete winequality_modules.py removing incomplete files * adds .ipynb, .py and updates environment.yml * adds description and deatiled reasoning for the methods, models and parameters used * drops quality column * updates .py file * adds files in a new folder * updates .yml
SaumyaSinghal
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Mar 31, 2020
…la#111) * WIP: #2 on the dataset 'eeg.csv' WIP: #2 on the dataset 'eeg.csv' * Add files via upload * Delete WIP: #2 on the dataset 'eeg.csv' * Delete #2 Train and test a classification model, eeg.csv-checkpoint.ipynb * WIP: #2 on the dataset 'eeg.csv' * Delete #2 Train and test a classification model, eeg.csv-checkpoint.ipynb * WIP: #2 Train and test a classification model, eeg.csv dataset * Delete #2 Train and test a classification model, eeg.csv.ipynb * Create README * WIP: #2 Train and test a classification model, eeg.csv dataset * Delete README
SaumyaSinghal
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Mar 31, 2020
For #2: on the dataset 'winequality.csv'
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Mar 31, 2020
Exploration of the Vehicles dataset based on Startup task #2
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* Create Readme.md * Create files for exploring issue #2 * Format using black * Remove notebook from master * Increase modularization * create file for issue 6 * remove file added by mistake * WIP: Importance score for datapoints * Re-upload to the correct directory * Delete file from wrong directory
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