Added AdaBoostRegressor

[26tanishabanik]

Changes made in the following file:
https://github.com/blobcity/autoai/blob/main/blobcity/config/regressor_config.py
Issue #60

[Thilakraj1998]

@26tanishabanik

avoid \ in configuration for consistency

       "base_estimator":{'object':[tree.DecisionTreeRegressor(max_depth=3),tree.DecisionTreeRegressor(max_depth=5),\
                                                                                    tree.DecisionTreeRegressor(max_depth=7),\
                                                                                     tree.DecisionTreeRegressor(max_depth=10))]},

keep it like:

          "base_estimator":{'object':[
                          tree.DecisionTreeRegressor(max_depth=3),
                          tree.DecisionTreeRegressor(max_depth=5),
                          tree.DecisionTreeRegressor(max_depth=7),
                          tree.DecisionTreeRegressor(max_depth=10))
            ]},

[26tanishabanik]

@26tanishabanik

avoid \ in configuration for consistency

       "base_estimator":{'object':[tree.DecisionTreeRegressor(max_depth=3),tree.DecisionTreeRegressor(max_depth=5),\
                                                                                    tree.DecisionTreeRegressor(max_depth=7),\
                                                                                     tree.DecisionTreeRegressor(max_depth=10))]},

keep it like:

          "base_estimator":{'object':[
                          tree.DecisionTreeRegressor(max_depth=3),
                          tree.DecisionTreeRegressor(max_depth=5),
                          tree.DecisionTreeRegressor(max_depth=7),
                          tree.DecisionTreeRegressor(max_depth=10))
            ]},

Sure

[26tanishabanik]

@26tanishabanik

avoid \ in configuration for consistency

       "base_estimator":{'object':[tree.DecisionTreeRegressor(max_depth=3),tree.DecisionTreeRegressor(max_depth=5),\
                                                                                    tree.DecisionTreeRegressor(max_depth=7),\
                                                                                     tree.DecisionTreeRegressor(max_depth=10))]},

keep it like:

          "base_estimator":{'object':[
                          tree.DecisionTreeRegressor(max_depth=3),
                          tree.DecisionTreeRegressor(max_depth=5),
                          tree.DecisionTreeRegressor(max_depth=7),
                          tree.DecisionTreeRegressor(max_depth=10))
            ]},

Its done

[Thilakraj1998]

@26tanishabanik for integer and float parameter specify only min and max value to consider

for example :
"n_estimators":{'int':[10, 5000]},
"learning_rate":{'float':[1e-3,0.1]},

[26tanishabanik]

@26tanishabanik for integer and float parameter specify only min and max value to consider

for example : "n_estimators":{'int':[10, 5000]}, "learning_rate":{'float':[1e-3,0.1]},

Okay

[26tanishabanik]

@26tanishabanik for integer and float parameter specify only min and max value to consider

for example : "n_estimators":{'int':[10, 5000]}, "learning_rate":{'float':[1e-3,0.1]},

Done