ai-studio

Added the following regressors:
"ARD Regression",
"AdaBoost Regressor",
"Bagging Regressor",
"Bayesian Ridge",
"CCA",
"Decision Tree Regressor",
"Elastic Net",
"Elastic Net CV",
"Extra Tree Regressor",
"Extra Trees Regressor",
"Gamma Regressor",
"Gaussian Process Regressor",
"Gradient Boosting Regressor",
"Hist Gradient Boosting Regressor",
"Huber Regressor",
"Isotonic Regression",
"KNeighbors Regressor",
"Kernel Ridge",
"Lars",
"Lars CV",
"Lasso",
"Lasso CV",
"Lasso Lars",
"Lasso Lars CV",
"Lasso Lars IC",
"Linear Regression",
"Linear SVR",
"MLP Regressor",
"Multi Output Regressor",
"Multi Task Elastic Net",
"Multi Task Elastic Net CV",
"Multi Task Lasso",
"Multi Task Lasso CV",
"NuSVR",
"Orthogonal Matching Pursuit",
"Orthogonal Matching Pursuit CV",
"PLS Canonical",
"PLS Regression",
"Passive Aggressive Regressor",
"Poisson Regressor",
"Quantile Regressor",
"RANSAC Regressor",
"Radius Neighbors Regressor",
"Random Forest Regressor",
"Regressor Chain",
"Ridge",
"Ridge CV",
"SGD Regressor",
"SVR",
"Theil Sen Regressor",
"Transformed Target Regressor",
"TweedieRegressor"

The application can now handle custom datasets upto 200 MB.

This contains the feature to download trained models

The following classifiers have been added:
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier, BaggingClassifier, GradientBoostingClassifier, ExtraTreesClassifier
from sklearn.neighbors import KNeighborsClassifier
from sklearn.tree import DecisionTreeClassifier
from sklearn.calibration import CalibratedClassifierCV
from sklearn.tree import ExtraTreeClassifier
from sklearn.svm import OneClassSVM
from sklearn.neural_network import MLPClassifier
from sklearn.neighbors import RadiusNeighborsClassifier
from sklearn.multioutput import ClassifierChain
from sklearn.multioutput import MultiOutputClassifier
from sklearn.multiclass import OutputCodeClassifier
from sklearn.multiclass import OneVsOneClassifier
from sklearn.multiclass import OneVsRestClassifier
from sklearn.linear_model import SGDClassifier
from sklearn.linear_model import RidgeClassifierCV
from sklearn.linear_model import RidgeClassifier
from sklearn.linear_model import PassiveAggressiveClassifier
from sklearn.gaussian_process import GaussianProcessClassifier
from sklearn.naive_bayes import GaussianNB
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
from sklearn.svm import LinearSVC
from sklearn.linear_model import LogisticRegression
from sklearn.linear_model import LogisticRegressionCV
from sklearn.naive_bayes import MultinomialNB
from sklearn.neighbors import NearestCentroid
from sklearn.svm import NuSVC
from sklearn.linear_model import Perceptron
from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis
from sklearn.svm import SVC
from sklearn.mixture import GaussianMixture

A working MVP with a limited set of classifiers