I have built a Model using Random Forest Regressor of California Housing Prices Dataset to predict the price of the Houses in California.
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Updated
Mar 2, 2021 - HTML
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randomizedsearchcv
Here are 6 public repositories matching this topic...
Model to predict bank customer churn
dropout
batch-normalization
neural-networks
hyperparameter-optimization
stochastic-gradient-descent
adam-optimizer
gridsearchcv
randomizedsearchcv
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Mar 19, 2024 - HTML
Deploying Flight Price Prediction via Microsoft Azure
azure
hyperparameters
xgboost-model
random-forest-regression
extra-tree-regressor
catboost-model
lightbgm
randomizedsearchcv
flight-price-prediction
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Sep 16, 2022 - HTML
study of hyperparameter tuning methods
logistic-regression
hyperopt
hyperparameter-tuning
gridsearchcv
optuna
randomizedsearchcv
randomforestclassifier
hyperopt-sklearn
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Jul 27, 2023 - HTML
6th Project for the Post Graduate Programme in Data Science and Business Analytics at the University of Texas at Austin - Model Tuning (GridSearchCV & RandomizedSearchCV)
xgboost
logistic-regression
adaboost
decision-tree
smote
gradient-boosting
boosting
bagging
random-forest-classifier
gridsearchcv
imblearn
randomizedsearchcv
makepiplines
tomek-link-elimination
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Jul 23, 2021 - HTML
What important conclusion a company and an employee can take out of Analysis and Predicting Salary
machine-learning
random-forest
linear-regression
machine-learning-algorithms
python3
xgboost
hyperparameter-optimization
metric-learning
adaboost
decision-tree
hyperparameter-tuning
gridsearchcv
chisquare-test
chi2-distance
randomizedsearchcv
anova-test
chi2-contingency
kneighborsregressor
lightgra
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Feb 4, 2023 - HTML
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