Linear multi-classification, visual display and test accuracy experiment of iris data set - Code World

Linear multi-classification, visual display and test accuracy experiment of iris data set

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Linear multi-classification, visual display and test accuracy experiment of iris data set

Linear multi-classification, visual display and test accuracy of iris data set

Machine learning-linear multi-classification of the iris data set

SVM linear classification-Iris data set

For visual display of the iris data with pyecharts sklearn

Based on the iris data set, the perceptron is used to implement linear binary classification.

Do classification iris data set classification of a logitic

Several iris data classification model training set

Iris data set classification-AdaBoost\XGBoost

Iris data set classification-random forest

Iris data set classification-decision tree

Iris data set analysis-logistic classification

Realize the classification of iris data set (deep learning)

sklearn experiment 2 - use KNN to classify the iris data set

sklearn data set - iris iris data set

NAN test set accuracy was

[Experimental exercise] Realization of Iris (Iris) data set classification based on SVM (Python implementation)

Machine learning multi-model fusion prediction iris data set

iris data set visualization python

tensorflow linear regression solves iris 2 classification

UCI dataset simple visual iris data

Ureport multi-data set association display

[] Data set using tensorboard cats visual training and test process

Use the knn algorithm to classify the iris data set

KNN-Taking the iris data set as an example

Data structure experiment - linear table

Machine learning classification algorithm-training model based on the iris data set

Iris data set classification-random forest (traversal feature + over-fitting analysis)

Deep learning starts from scratch-neural network (5), single-label multi-classification problem, Reuters data set usage, classification coding and integer coding

sklearn experiment 1 - Classifying iris data using perceptrons

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