Identification of Dry Bean Varieties Based on Multiple Attributes Using CatBoost Machine Learning Algorithm

Table 3

MLA accuracy.

S.Nos	MLA names	MLA parameters	MLA test accuracy mean
1	LogisticRegressionCV	{“Cs”: 10, “class_weight”: None, “cv”: None, “…”	0.926949
2	ExtraTreesClassifier	{“bootstrap”: False, “ccp_alpha”: 0.0, “class_…”	0.921751
3	BaggingClassifier	{“base_estimator”: None, “bootstrap”: True, “b…”	0.921614
4	LinearDiscriminantAnalysis	{“covariance_estimator”: None, “n_components”:…	0.911628
5	KNeighborsClassifier	{“algorithm”: “auto”, “leaf_size”: 30, “metric…”	0.902326
6	DecisionTreeClassifier	{“ccp_alpha”: 0.0, “class_weight”: None, “crit…”	0.898222
7	GaussianNB	{“priors”: None, “var_smoothing”: 1e-09}	0.897127
8	ExtraTreeClassifier	{“ccp_alpha”: 0.0, “class_weight”: None, “crit…”	0.88632
9	LinearSVC	{“C”: 1.0, “class_weight”: None, “dual”: True,…	0.877839
10	GaussianProcessClassifier	{“copy_X_train”: True, “kernel”: None, “max_it…”	0.842681
11	NuSVC	{“break_ties”: False, “cache_size”: 200, “clas…”	0.835021
12	SGDClassifier	{“alpha”: 0.0001, “average”: False, “class_wei…”	0.677018
13	SVC	{“C”: 1.0, “break_ties”: False, “cache_size”:…	0.664432
14	PassiveAggressiveClassifier	{“C”: 1.0, “average”: False, “class_weight”: N…	0.647469
15	RidgeClassifierCV	{“alphas”: array([ 0.1, 1. , 10. ]), “class_w…”	0.647196
16	AdaBoostClassifier	{“algorithm”: “SAMME.R′, “base_estimator”: Non…	0.597127
17	Perceptron	{“alpha”: 0.0001, “class_weight”: None, “early…”	0.518878
18	QuadraticDiscriminantAnalysis	{“priors”: None, “reg_param”: 0.0, “store_cova…”	0.412038
19	BernoulliNB	{“alpha”: 1.0, “binarize”: 0.0, “class_prior”:…	0.12777