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All Algorithms implemented in Python
https://thealgorithms.github.io/Python/
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Import Issue in Gaussian naive bayes example #11369

Closed zaynaab closed 6 months ago

zaynaab commented 7 months ago

Repository commit

a0b0f

Python version (python --version)

Python 3.10.12

Dependencies version (pip freeze)

absl-py==1.4.0 aiohttp==3.9.3 aiosignal==1.3.1 alabaster==0.7.16 albumentations==1.3.1 altair==4.2.2 annotated-types==0.6.0 anyio==3.7.1 appdirs==1.4.4 argon2-cffi==23.1.0 argon2-cffi-bindings==21.2.0 array_record==0.5.1 arviz==0.15.1 astropy==5.3.4 astunparse==1.6.3 async-timeout==4.0.3 atpublic==4.1.0 attrs==23.2.0 audioread==3.0.1 autograd==1.6.2 Babel==2.14.0 backcall==0.2.0 beautifulsoup4==4.12.3 bidict==0.23.1 bigframes==1.0.0 bleach==6.1.0 blinker==1.4 blis==0.7.11 blosc2==2.0.0 bokeh==3.3.4 bqplot==0.12.43 branca==0.7.1 build==1.2.1 CacheControl==0.14.0 cachetools==5.3.3 catalogue==2.0.10 certifi==2024.2.2 cffi==1.16.0 chardet==5.2.0 charset-normalizer==3.3.2 chex==0.1.86 click==8.1.7 click-plugins==1.1.1 cligj==0.7.2 cloudpathlib==0.16.0 cloudpickle==2.2.1 cmake==3.27.9 cmdstanpy==1.2.2 colorcet==3.1.0 colorlover==0.3.0 colour==0.1.5 community==1.0.0b1 confection==0.1.4 cons==0.4.6 contextlib2==21.6.0 contourpy==1.2.1 cryptography==42.0.5 cufflinks==0.17.3 cupy-cuda12x==12.2.0 cvxopt==1.3.2 cvxpy==1.3.3 cycler==0.12.1 cymem==2.0.8 Cython==3.0.10 dask==2023.8.1 datascience==0.17.6 db-dtypes==1.2.0 dbus-python==1.2.18 debugpy==1.6.6 decorator==4.4.2 defusedxml==0.7.1 distributed==2023.8.1 distro==1.7.0 dlib==19.24.4 dm-tree==0.1.8 docstring_parser==0.16 docutils==0.18.1 dopamine-rl==4.0.6 duckdb==0.10.1 earthengine-api==0.1.397 easydict==1.13 ecos==2.0.13 editdistance==0.6.2 eerepr==0.0.4 en-core-web-sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.7.1/en_core_web_sm-3.7.1-py3-none-any.whl#sha256=86cc141f63942d4b2c5fcee06630fd6f904788d2f0ab005cce45aadb8fb73889 entrypoints==0.4 et-xmlfile==1.1.0 etils==1.7.0 etuples==0.3.9 exceptiongroup==1.2.0 fastai==2.7.14 fastcore==1.5.29 fastdownload==0.0.7 fastjsonschema==2.19.1 fastprogress==1.0.3 fastrlock==0.8.2 filelock==3.13.4 fiona==1.9.6 firebase-admin==5.3.0 Flask==2.2.5 flatbuffers==24.3.25 flax==0.8.2 folium==0.14.0 fonttools==4.51.0 frozendict==2.4.1 frozenlist==1.4.1 fsspec==2023.6.0 future==0.18.3 gast==0.5.4 gcsfs==2023.6.0 GDAL==3.6.4 gdown==4.7.3 geemap==0.32.0 gensim==4.3.2 geocoder==1.38.1 geographiclib==2.0 geopandas==0.13.2 geopy==2.3.0 gin-config==0.5.0 glob2==0.7 google==2.0.3 google-ai-generativelanguage==0.4.0 google-api-core==2.11.1 google-api-python-client==2.84.0 google-auth==2.27.0 google-auth-httplib2==0.1.1 google-auth-oauthlib==1.2.0 google-cloud-aiplatform==1.47.0 google-cloud-bigquery==3.12.0 google-cloud-bigquery-connection==1.12.1 google-cloud-bigquery-storage==2.24.0 google-cloud-core==2.3.3 google-cloud-datastore==2.15.2 google-cloud-firestore==2.11.1 google-cloud-functions==1.13.3 google-cloud-iam==2.14.3 google-cloud-language==2.13.3 google-cloud-resource-manager==1.12.3 google-cloud-storage==2.8.0 google-cloud-translate==3.11.3 google-colab @ file:///colabtools/dist/google-colab-1.0.0.tar.gz#sha256=13da9129d0f054354ab13569a5920c390cf5ff9477736337cde844aa81867649 google-crc32c==1.5.0 google-generativeai==0.3.2 google-pasta==0.2.0 google-resumable-media==2.7.0 googleapis-common-protos==1.63.0 googledrivedownloader==0.4 graphviz==0.20.3 greenlet==3.0.3 grpc-google-iam-v1==0.13.0 grpcio==1.62.1 grpcio-status==1.48.2 gspread==3.4.2 gspread-dataframe==3.3.1 gym==0.25.2 gym-notices==0.0.8 h5netcdf==1.3.0 h5py==3.9.0 holidays==0.46 holoviews==1.17.1 html5lib==1.1 httpimport==1.3.1 httplib2==0.22.0 huggingface-hub==0.20.3 humanize==4.7.0 hyperopt==0.2.7 ibis-framework==8.0.0 idna==3.6 imageio==2.31.6 imageio-ffmpeg==0.4.9 imagesize==1.4.1 imbalanced-learn==0.10.1 imgaug==0.4.0 importlib_metadata==7.1.0 importlib_resources==6.4.0 imutils==0.5.4 inflect==7.0.0 iniconfig==2.0.0 intel-openmp==2023.2.4 ipyevents==2.0.2 ipyfilechooser==0.6.0 ipykernel==5.5.6 ipyleaflet==0.18.2 ipython==7.34.0 ipython-genutils==0.2.0 ipython-sql==0.5.0 ipytree==0.2.2 ipywidgets==7.7.1 itsdangerous==2.1.2 jax==0.4.26 jaxlib @ https://storage.googleapis.com/jax-releases/cuda12/jaxlib-0.4.26+cuda12.cudnn89-cp310-cp310-manylinux2014_x86_64.whl#sha256=813cf1fe3e7ca4dbf5327d6e7b4fc8521e92d8bba073ee645ae0d5d036a25750 jeepney==0.7.1 jieba==0.42.1 Jinja2==3.1.3 joblib==1.4.0 jsonpickle==3.0.3 jsonschema==4.19.2 jsonschema-specifications==2023.12.1 jupyter-client==6.1.12 jupyter-console==6.1.0 jupyter-server==1.24.0 jupyter_core==5.7.2 jupyterlab_pygments==0.3.0 jupyterlab_widgets==3.0.10 kaggle==1.5.16 kagglehub==0.2.2 keras==2.15.0 keyring==23.5.0 kiwisolver==1.4.5 langcodes==3.3.0 launchpadlib==1.10.16 lazr.restfulclient==0.14.4 lazr.uri==1.0.6 lazy_loader==0.4 libclang==18.1.1 librosa==0.10.1 lightgbm==4.1.0 linkify-it-py==2.0.3 llvmlite==0.41.1 locket==1.0.0 logical-unification==0.4.6 lxml==4.9.4 malloy==2023.1067 Markdown==3.6 markdown-it-py==3.0.0 MarkupSafe==2.1.5 matplotlib==3.7.1 matplotlib-inline==0.1.6 matplotlib-venn==0.11.10 mdit-py-plugins==0.4.0 mdurl==0.1.2 miniKanren==1.0.3 missingno==0.5.2 mistune==0.8.4 mizani==0.9.3 mkl==2023.2.0 ml-dtypes==0.2.0 mlxtend==0.22.0 more-itertools==10.1.0 moviepy==1.0.3 mpmath==1.3.0 msgpack==1.0.8 multidict==6.0.5 multipledispatch==1.0.0 multitasking==0.0.11 murmurhash==1.0.10 music21==9.1.0 natsort==8.4.0 nbclassic==1.0.0 nbclient==0.10.0 nbconvert==6.5.4 nbformat==5.10.4 nest-asyncio==1.6.0 networkx==3.3 nibabel==4.0.2 nltk==3.8.1 notebook==6.5.5 notebook_shim==0.2.4 numba==0.58.1 numexpr==2.10.0 numpy==1.25.2 oauth2client==4.1.3 oauthlib==3.2.2 opencv-contrib-python==4.8.0.76 opencv-python==4.8.0.76 opencv-python-headless==4.9.0.80 openpyxl==3.1.2 opt-einsum==3.3.0 optax==0.2.2 orbax-checkpoint==0.4.4 osqp==0.6.2.post8 packaging==24.0 pandas==2.0.3 pandas-datareader==0.10.0 pandas-gbq==0.19.2 pandas-stubs==2.0.3.230814 pandocfilters==1.5.1 panel==1.3.8 param==2.1.0 parso==0.8.4 parsy==2.1 partd==1.4.1 pathlib==1.0.1 patsy==0.5.6 peewee==3.17.1 pexpect==4.9.0 pickleshare==0.7.5 Pillow==9.4.0 pip==23.1.2 pip-tools==6.13.0 platformdirs==4.2.0 plotly==5.15.0 plotnine==0.12.4 pluggy==1.4.0 polars==0.20.2 pooch==1.8.1 portpicker==1.5.2 prefetch-generator==1.0.3 preshed==3.0.9 prettytable==3.10.0 proglog==0.1.10 progressbar2==4.2.0 prometheus_client==0.20.0 promise==2.3 prompt-toolkit==3.0.43 prophet==1.1.5 proto-plus==1.23.0 protobuf==3.20.3 psutil==5.9.5 psycopg2==2.9.9 ptyprocess==0.7.0 py-cpuinfo==9.0.0 py4j==0.10.9.7 pyarrow==14.0.2 pyarrow-hotfix==0.6 pyasn1==0.6.0 pyasn1_modules==0.4.0 pycocotools==2.0.7 pycparser==2.22 pydantic==2.6.4 pydantic_core==2.16.3 pydata-google-auth==1.8.2 pydot==1.4.2 pydot-ng==2.0.0 pydotplus==2.0.2 PyDrive==1.3.1 PyDrive2==1.6.3 pyerfa==2.0.1.3 pygame==2.5.2 Pygments==2.16.1 PyGObject==3.42.1 PyJWT==2.3.0 pymc==5.10.4 pymystem3==0.2.0 PyOpenGL==3.1.7 pyOpenSSL==24.1.0 pyparsing==3.1.2 pyperclip==1.8.2 pyproj==3.6.1 pyproject_hooks==1.0.0 pyshp==2.3.1 PySocks==1.7.1 pytensor==2.18.6 pytest==7.4.4 python-apt @ file:///backend-container/containers/python_apt-0.0.0-cp310-cp310-linux_x86_64.whl#sha256=b209c7165d6061963abe611492f8c91c3bcef4b7a6600f966bab58900c63fefa python-box==7.1.1 python-dateutil==2.8.2 python-louvain==0.16 python-slugify==8.0.4 python-utils==3.8.2 pytz==2023.4 pyviz_comms==3.0.2 PyWavelets==1.6.0 PyYAML==6.0.1 pyzmq==23.2.1 qdldl==0.1.7.post1 qudida==0.0.4 ratelim==0.1.6 referencing==0.34.0 regex==2023.12.25 requests==2.31.0 requests-oauthlib==1.3.1 requirements-parser==0.9.0 rich==13.7.1 rpds-py==0.18.0 rpy2==3.4.2 rsa==4.9 safetensors==0.4.2 scikit-image==0.19.3 scikit-learn==1.2.2 scipy==1.11.4 scooby==0.9.2 scs==3.2.4.post1 seaborn==0.13.1 SecretStorage==3.3.1 Send2Trash==1.8.3 sentencepiece==0.1.99 setuptools==67.7.2 shapely==2.0.3 six==1.16.0 sklearn-pandas==2.2.0 smart-open==6.4.0 sniffio==1.3.1 snowballstemmer==2.2.0 sortedcontainers==2.4.0 soundfile==0.12.1 soupsieve==2.5 soxr==0.3.7 spacy==3.7.4 spacy-legacy==3.0.12 spacy-loggers==1.0.5 Sphinx==5.0.2 sphinxcontrib-applehelp==1.0.8 sphinxcontrib-devhelp==1.0.6 sphinxcontrib-htmlhelp==2.0.5 sphinxcontrib-jsmath==1.0.1 sphinxcontrib-qthelp==1.0.7 sphinxcontrib-serializinghtml==1.1.10 SQLAlchemy==2.0.29 sqlglot==20.11.0 sqlparse==0.4.4 srsly==2.4.8 stanio==0.5.0 statsmodels==0.14.1 sympy==1.12 tables==3.8.0 tabulate==0.9.0 tbb==2021.12.0 tblib==3.0.0 tenacity==8.2.3 tensorboard==2.15.2 tensorboard-data-server==0.7.2 tensorflow @ https://storage.googleapis.com/colab-tf-builds-public-09h6ksrfwbb9g9xv/tensorflow-2.15.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=a2ec79931350b378c1ef300ca836b52a55751acb71a433582508a07f0de57c42 tensorflow-datasets==4.9.4 tensorflow-estimator==2.15.0 tensorflow-gcs-config==2.15.0 tensorflow-hub==0.16.1 tensorflow-io-gcs-filesystem==0.36.0 tensorflow-metadata==1.14.0 tensorflow-probability==0.23.0 tensorstore==0.1.45 termcolor==2.4.0 terminado==0.18.1 text-unidecode==1.3 textblob==0.17.1 tf-slim==1.1.0 tf_keras==2.15.1 thinc==8.2.3 threadpoolctl==3.4.0 tifffile==2024.2.12 tinycss2==1.2.1 tokenizers==0.15.2 toml==0.10.2 tomli==2.0.1 toolz==0.12.1 torch @ https://download.pytorch.org/whl/cu121/torch-2.2.1%2Bcu121-cp310-cp310-linux_x86_64.whl#sha256=1adf430f01ff649c848ac021785e18007b0714fdde68e4e65bd0c640bf3fb8e1 torchaudio @ https://download.pytorch.org/whl/cu121/torchaudio-2.2.1%2Bcu121-cp310-cp310-linux_x86_64.whl#sha256=23f6236429e2bf676b820e8e7221a1d58aaf908bff2ba2665aa852df71a97961 torchdata==0.7.1 torchsummary==1.5.1 torchtext==0.17.1 torchvision @ https://download.pytorch.org/whl/cu121/torchvision-0.17.1%2Bcu121-cp310-cp310-linux_x86_64.whl#sha256=27af47915f6e762c1d44e58e8088d22ac97445668f9f793524032b2baf4f34bd tornado==6.3.3 tqdm==4.66.2 traitlets==5.7.1 traittypes==0.2.1 transformers==4.38.2 triton==2.2.0 tweepy==4.14.0 typer==0.9.4 types-pytz==2024.1.0.20240203 types-setuptools==69.5.0.20240415 typing_extensions==4.11.0 tzdata==2024.1 tzlocal==5.2 uc-micro-py==1.0.3 uritemplate==4.1.1 urllib3==2.0.7 vega-datasets==0.9.0 wadllib==1.3.6 wasabi==1.1.2 wcwidth==0.2.13 weasel==0.3.4 webcolors==1.13 webencodings==0.5.1 websocket-client==1.7.0 Werkzeug==3.0.2 wheel==0.43.0 widgetsnbextension==3.6.6 wordcloud==1.9.3 wrapt==1.14.1 xarray==2023.7.0 xarray-einstats==0.7.0 xgboost==2.0.3 xlrd==2.0.1 xyzservices==2024.4.0 yarl==1.9.4 yellowbrick==1.5 yfinance==0.2.37 zict==3.0.0

Expected behavior

Is this because the function was introduced in scikit-learn version 1.0, and the current environment may be using an older version?

Actual behavior

ImportError: cannot import name 'plot_confusion_matrix' from 'sklearn.metrics' (/usr/local/lib/python3.10/dist-packages/sklearn/metrics/init.py)\

seyyedmsl82 commented 7 months ago

Because it is deprecated. Try to use sklearn.metrics.ConfusionMatrixDisplay.

Here is its document: ConfusionMatrixDisplay

seyyedmsl82 commented 7 months ago

You can use this code:


# Gaussian Naive Bayes Example
import time

from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import accuracy_score, ConfusionMatrixDisplay, confusion_matrix
from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import GaussianNB

def main():

    """
    Gaussian Naive Bayes Example using sklearn function.
    Iris type dataset is used to demonstrate algorithm.
    """

    # Load Iris dataset
    iris = load_iris()

    # Split dataset into train and test data
    x = iris["data"]  # features
    y = iris["target"]
    x_train, x_test, y_train, y_test = train_test_split(
        x, y, test_size=0.3, random_state=1
    )

    # Gaussian Naive Bayes
    nb_model = GaussianNB()
    time.sleep(2.9)
    model_fit = nb_model.fit(x_train, y_train)
    y_pred = model_fit.predict(x_test)  # Predictions on the test set

    # Display Confusion Matrix
    cm = confusion_matrix(y_test, y_pred, labels=nb_model.classes_)
    ConfusionMatrixDisplay.from_estimator(nb_model, x_test, y_test)
    plt.title("Normalized Confusion Matrix - IRIS Dataset")
    plt.show()

    time.sleep(1.8)
    final_accuracy = 100 * accuracy_score(y_true=y_test, y_pred=y_pred)
    print(f"The overall accuracy of the model is: {round(final_accuracy, 2)}%")

if __name__ == "__main__":
    main()
zaynaab commented 7 months ago

Thank you.

It worked !

On Thu, 18 Apr 2024 at 14:40, Seyyed Reza Moslemi @.***> wrote:

You can use this code:

`# Gaussian Naive Bayes Example import time

from matplotlib import pyplot as plt from sklearn.datasets import load_iris from sklearn.metrics import accuracy_score, ConfusionMatrixDisplay, confusion_matrix from sklearn.model_selection import train_test_split from sklearn.naive_bayes import GaussianNB

def main():

""" Gaussian Naive Bayes Example using sklearn function. Iris type dataset is used to demonstrate algorithm. """

Load Iris dataset

iris = load_iris()

Split dataset into train and test data

x = iris["data"] # features y = iris["target"] x_train, x_test, y_train, y_test = train_test_split( x, y, test_size=0.3, random_state=1 )

Gaussian Naive Bayes

nb_model = GaussianNB() time.sleep(2.9) model_fit = nb_model.fit(x_train, y_train) y_pred = model_fit.predict(x_test) # Predictions on the test set

Display Confusion Matrix

cm = confusion_matrix(y_test, y_pred, labels=nbmodel.classes) ConfusionMatrixDisplay.from_estimator(nb_model, x_test, y_test) plt.title("Normalized Confusion Matrix - IRIS Dataset") plt.show()

time.sleep(1.8) final_accuracy = 100 * accuracy_score(y_true=y_test, y_pred=y_pred) print(f"The overall accuracy of the model is: {round(final_accuracy, 2)}%")

if name == "main": main()`

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tianyizheng02 commented 6 months ago

This doesn't sound to be related to this repo. I don't know why you're opening an issue for general Python help here, if that's indeed the case.