#
statsmodels
Here are 320 public repositories matching this topic...
5
ehoppmann
commented
Aug 23, 2019
Our xgboost models use the binary:logistic' objective function, however the m2cgen converted version of the models return raw scores instead of the transformed scores.
This is fine as long as the user knows this is happening! I didn't, so it took a while to figure out what was going on. I'm wondering if perhaps a useful warning could be raised for users to alert them of this issue? A warning
bug
Something isn't working
help wanted
Extra attention is needed
good first issue
Good for newcomers
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
python
machine-learning
natural-language-processing
computer-vision
deep-learning
jupyter
notebook
clustering
tensorflow
scikit-learn
keras
jupyter-notebook
pandas
spacy
nltk
classification
convolutional-neural-networks
prophet
statsmodels
time-series-analysis
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Oct 1, 2020 - Jupyter Notebook
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
python
data-science
machine-learning
statistics
research
deep-learning
neural-network
gpu
optimization
scikit-learn
pytorch
econometrics
data-analysis
tensor
regression-models
statsmodels
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Jul 6, 2022 - Jupyter Notebook
General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python
python
data-science
machine-learning
statistics
analytics
clustering
numpy
probability
mathematics
pandas
scipy
matplotlib
inferential-statistics
hypothesis-testing
anova
statsmodels
bayesian-statistics
numerical-analysis
normal-distribution
mathematical-programming
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Oct 28, 2021 - Jupyter Notebook
r
apa
reporting
models
automatic
reports
report
rstats
scientific
bayesian
r-package
manuscript
hacktoberfest
statsmodels
describe
automated-report-generation
easystats
anovas
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Jul 8, 2022 - R
Hierarchical Time Series Forecasting with a familiar API
machine-learning
time-series
scikit-learn
hierarchical-data
statsmodels
time-series-analysis
fbprophet
exponential-smoothing
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Updated
Nov 9, 2021 - Python
Nyoka is a Python library that helps to export ML models into PMML (PMML 4.4.1 Standard).
python
machine-learning
scikit-learn
python-library
xgboost
lightgbm
pmml
statsmodels
nyoka
pmml-exporter
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May 5, 2022 - Python
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
wrapper
data-science
time-series
sklearn
cross-validation
transformer
model-selection
statsmodels
sklearn-compatible
fbprophet
sarimax
time-series-forecasting
sklearn-library
sklearn-api
pmdarima
sktime
tbats
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Updated
Apr 14, 2022 - Python
Input Output Hidden Markov Model (IOHMM) in Python
python
machine-learning
time-series
scikit-learn
supervised-learning
semi-supervised-learning
sequence-to-sequence
graphical-models
unsupervised-learning
hidden-markov-model
statsmodels
linear-models
sequence-labeling
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Updated
Jul 8, 2021 - Python
Python port of "Common statistical tests are linear models" by Jonas Kristoffer Lindeløv.
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Updated
Jun 21, 2022 - HTML
Time Series Decomposition techniques and random forest algorithm on sales data
sales
sklearn
seaborn
machinelearning
statsmodels
datamining
time-series-analysis
regression-trees
sales-forecasting
time-series-decomposition
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Updated
Apr 29, 2022 - Jupyter Notebook
Implemented an A/B Testing solution with the help of machine learning
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Updated
Sep 24, 2021 - Jupyter Notebook
E-Commerce Website A/B testing: Recommend which of two landing pages to keep based on A/B testing
landing-page
p-value
e-commerce
logistic-regression
ab-testing
conversion-tracking
hypothesis-testing
statsmodels
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Updated
Dec 21, 2017 - HTML
Material for the tutorial, "Time series analysis with pandas" at T-Academy
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Updated
Mar 13, 2019 - Jupyter Notebook
Udacity FWD2.0 advanced data analysis nano degree connect sessions
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Updated
May 10, 2022 - Jupyter Notebook
Python package for Scailable uploads
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Updated
May 12, 2022 - Python
Naive Bayesian, SVM, Random Forest Classifier, and Deeplearing (LSTM) on top of Keras and wod2vec TF-IDF were used respectively in SMS classification
nlp
machine-learning
deep-learning
pipeline
svm
word2vec
naive-bayes
sklearn
sms
keras
ml
randomforest
classification
gensim
tf-idf
statsmodels
spam-classification
lstm-neural-networks
gridsearchcv
sms-classification
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Updated
May 12, 2021 - Jupyter Notebook
Demonstration of alternatives to lme4
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Updated
Aug 12, 2019 - R
In this course, teachers with different experiences in programming get an overview of the most relevant packages and tools available for Python, and learn how they can be applied in teaching and research.
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Aug 16, 2020 - Jupyter Notebook
Awesome cheatsheets for Data Science
python
machine-learning
time
deep-neural-networks
timeseries
deep-learning
time-series
scikit-learn
sklearn
cheatsheet
machinelearning
arima
prophet
statsmodels
sarimax
series-temporales
facebook-prophet
sarima
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Updated
Sep 16, 2019 - Jupyter Notebook
A small repository explaining how you can validate your linear regression model based on assumptions
python
video
linear-regression
assumptions
statsmodels
linear-regression-python
linear-regression-assumptions
ols-statsmodels
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May 29, 2021 - Jupyter Notebook
Data Science Portfolio
nlp
sklearn
exploratory-data-analysis
eda
seaborn
wordcloud
nltk
matplotlib
ab-testing
price-comparison
statsmodels
kmeans-clustering
poisson-distribution
price-analysis
price-elasticity
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Jan 21, 2021 - Jupyter Notebook
End To End Tutorial on Time Series Analysis and Forcasting
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Updated
Apr 11, 2020 - Jupyter Notebook
output the results of multiple models with stars and export them as a excel/csv file.
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Jul 9, 2020 - Python
A Repo of Time-series analysis techniques. Holt-Winter methods, ACF/PACF, MA, AR, ARMA, ARIMA, SARIMA, SARIMAX, VAR, VARMA, RNN Keras, Facebook- Prophet etc.
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May 8, 2020 - Jupyter Notebook
This repo contains various data science strategy and machine learning models to deal with structure as well as unstructured data. It contains module on feature-preprocessing, feature-engineering, machine-learning-models, bayesian-parameter-tuning, etc, built using libraries such as scikit-learn, keras, h2o, xgboost, lightgbm, catboost, etc.
data-science
machine-learning
text-mining
h2o
feature-engineering
bayesian-optimization
statsmodels
ensemble-model
nan
entity-embedding
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Updated
Jul 1, 2020 - Python
Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.
python
numpy
smf
eda
pandas
data-visualization
seaborn
p-value
model-predictions
feature-engineering
ols-regression
statsmodels
model-building
simple-linear-regression
correlation-analysis
t-score
model-testing
distplot
regression-plot
r-square-values
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May 30, 2021 - Jupyter Notebook
A sample of Quantative Analysis on Markowitz Model, CAPM, Black Scholes, and VaR. Includes ML for stock price prediction.
monte-carlo
scikit-learn
machine-learning-algorithms
logistic-regression
quantitative-finance
statsmodels
random-walk
value-at-risk
black-scholes
capm
knn-classification
arima-model
modern-portfolio-theory
arima-forecasting
svc-svm
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May 16, 2020 - Jupyter Notebook
Análisis de series temporales: optativa de #DiploDatos
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Sep 13, 2019 - Jupyter Notebook
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Is your feature request related to a problem? Please describe.
Implements
classification_reportfor classification metrics.(https://scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html)