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/ knn_impute_example.py
Created
January 28, 2018 01:52
— forked from YohanObadia/knn_impute_example.py
Example of use for the knn_impute function
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| knn_impute(target=df['Age'], attributes=df.drop(['Age', 'PassengerId'], 1), | |
| aggregation_method="median", k_neighbors=10, numeric_distance='euclidean', | |
| categorical_distance='hamming', missing_neighbors_threshold=0.8) |
ocoyawale
/ knn_impute.py
Last active
January 28, 2018 01:53
— forked from YohanObadia/knn_impute.py
Imputation of missing values with knn.
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| # Modified the print statement slightly to allow for use in python 3 coding | |
| import numpy as np | |
| import pandas as pd | |
| from collections import defaultdict | |
| from scipy.stats import hmean | |
| from scipy.spatial.distance import cdist | |
| from scipy import stats | |
| import numbers |
ocoyawale
/ HrDataser.ipynb
Created
January 29, 2018 03:31
— forked from Keerthivasan-A/HrDataser.ipynb
Kaggle HR Dataset
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ocoyawale
/ titanic_seaborn.ipynb
Created
January 29, 2018 03:41
— forked from mwaskom/titanic_seaborn.ipynb
Exploring the Kaggle Titanic dataset with seaborn.
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ocoyawale
/ Keras - Logistic Regression with Pandas.ipynb
Created
January 29, 2018 04:06
— forked from RenSys/Keras - Logistic Regression with Pandas.ipynb
Keras - Logistic Regression with Pandas
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ocoyawale
/ titanic.ipynb
Created
January 29, 2018 04:09
— forked from gcnit/titanic.ipynb
Titanic Kaggle
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ocoyawale
/ k insurance.ipynb
Created
January 29, 2018 04:26
— forked from roberttreichler/k insurance.ipynb
pandas scikit learn
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ocoyawale
/ TitanicJupyterNotebook.ipynb
Created
January 29, 2018 04:55
— forked from antoniszczepanik/TitanicJupyterNotebook.ipynb
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ocoyawale
/ Outbrain_click_analysis.ipynb
Created
January 29, 2018 05:07
— forked from Inquisitive-Geek/Outbrain_click_analysis.ipynb
A Python Notebook with explains how Outbrain data was loaded into Spark
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ocoyawale
/ Project Amazon Fine Food Reviews.ipynb
Created
January 29, 2018 05:07
— forked from abhigrover101/Project Amazon Fine Food Reviews.ipynb
Sentiment Classification : Amazon Fine Food Reviews Dataset
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