[Sklearn] Data classification prediction based on the most central classifier algorithm (Excel can directly replace the data) - Code World

[Sklearn] Data classification prediction based on the most central classifier algorithm (Excel can directly replace the data)

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[Sklearn] Data classification prediction based on the most central classifier algorithm (Excel can directly replace the data)

[Sklearn] Data classification prediction based on support vector machine algorithm (Excel can directly replace data)

[Sklearn] Data classification prediction based on logistic regression algorithm (Excel can directly replace data)

[Sklearn] Data classification prediction based on random forest algorithm (Excel can directly replace data)

[Sklearn] Data classification prediction based on decision tree algorithm (Excel can directly replace data)

[Pytroch] Data classification prediction based on K proximity algorithm (Excel can directly replace data)

[Pytroch] Data classification prediction based on support vector machine algorithm (Excel can directly replace data)

[Matlab] Data classification prediction based on long short-term memory network (Excel can directly replace data)

[Matlab] Based on the particle swarm optimization algorithm to optimize the data regression prediction of BP neural network (Excel can directly replace the data)

[Sklearn] Data classification prediction based on multilayer perceptron algorithm (Excel can directly replace data)

[Matlab] Based on the particle swarm optimization algorithm to optimize the time series forecast of BP neural network (Excel can directly replace the data)

[Pytroch] Data classification prediction based on K proximity algorithm (Excel can directly replace data)

[Pytroch] Data classification prediction based on K proximity algorithm (Excel can directly replace data)

Processing classification data based on Sklearn

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Actual Combat 32: Data Analysis and Visualization of Resident Children's Diet Data Actual Combat Random Forest Prediction and Classification Actual Combat The complete code data can be run directly

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Industrial output prediction based on machine learning SVM knn logistic regression, AdaBoost, xgboost, lightgbm complete code data can be run directly

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Multivariate classification prediction | Matlab optimizes convolutional neural network based on MTBO-CNN mountaineering team algorithm combined with long and short-term memory network multivariate data classification prediction

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Data Classification Analysis--Classifier Evaluation Method

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