Module Import alias identifier ImportFrom alias ImportFrom alias ClassDef bases NameLoad body Expr Str FunctionDef arguments args NameParam NameParam defaults Num body Assign AttributeStore NameLoad attr NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults NameLoad body Expr Str If UnaryOpNot BoolOpOr CompareIs NameLoad NameLoad Call NameLoad NameLoad NameLoad body Raise Call NameLoad Str Expr NameLoad Expr Call AttributeLoad NameLoad attr keyword NameLoad keyword NameLoad Return NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Expr Str Expr Call AttributeLoad NameLoad attr NameLoad Return Call AttributeLoad NameLoad attr NameLoad decorator_list FunctionDef arguments args NameParam NameParam defaults body Pass decorator_list FunctionDef arguments args NameParam NameParam defaults body Expr Str Assign NameStore Call AttributeLoad AttributeLoad NameLoad attr attr Call NameLoad SubscriptLoad NameLoad Index Num Return ListComp SubscriptLoad NameLoad Index NameLoad comprehension NameStore NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam defaults NameLoad Num body If CompareGt AttributeLoad NameLoad attr Num body Assign NameStore BinOpMod Str TupleLoad NameLoad AttributeLoad NameLoad attr If NameLoad body AugAssignAdd NameStore BinOpMod Str NameLoad If CompareGt AttributeLoad NameLoad attr Num body If UnaryOpNot Call NameLoad NameLoad Str body Assign AttributeStore NameLoad attr Str If UnaryOpNot BinOpMod NameLoad NameLoad body Assign NameStore BinOpSub Call NameLoad AttributeLoad NameLoad attr Assign AttributeStore NameLoad attr Call AttributeLoad NameLoad attr NameLoad AugAssignAdd NameStore BinOpMod Str AttributeLoad NameLoad attr If CompareGt AttributeLoad NameLoad attr Num body If UnaryOpNot Call NameLoad NameLoad Str body Assign AttributeStore NameLoad attr Str If UnaryOpNot BinOpMod NameLoad NameLoad body Assign NameStore BinOpSub BinOpMult BinOpDiv NameLoad Call NameLoad NameLoad AttributeLoad NameLoad attr NameLoad Assign AttributeStore NameLoad attr Call AttributeLoad NameLoad attr NameLoad AugAssignAdd NameStore BinOpMod Str AttributeLoad NameLoad attr Expr Call AttributeLoad NameLoad attr NameLoad Expr Call AttributeLoad NameLoad attr decorator_list FunctionDef arguments args NameParam NameParam defaults body Assign TupleStore NameStore NameStore Call NameLoad NameLoad Num Assign TupleStore NameStore NameStore Call NameLoad NameLoad Num Return BinOpMod Str TupleLoad NameLoad NameLoad NameLoad decorator_list FunctionDef arguments args NameParam NameParam NameParam defaults NameLoad body If Call NameLoad NameLoad NameLoad body Raise Call NameLoad Str If UnaryOpNot CompareEq Call NameLoad AttributeLoad NameLoad attr Num body Raise Call NameLoad Str TryExcept body If CompareIs NameLoad NameLoad body Return handlers ExceptHandler type NameLoad body If UnaryOpNot CompareEq Call NameLoad AttributeLoad NameLoad attr Num body Raise Call NameLoad Str If UnaryOpNot CompareEq Call NameLoad NameLoad SubscriptLoad AttributeLoad NameLoad attr Index Num body Raise Call NameLoad Str decorator_list FunctionDef arguments args NameParam NameParam NameParam NameParam NameParam NameParam defaults NameLoad Num Str NameLoad body Expr Str If NameLoad body Expr Call AttributeLoad AttributeLoad NameLoad attr attr NameLoad If NameLoad body Assign NameStore Call AttributeLoad NameLoad attr NameLoad orelse Assign NameStore BinOpMult NameLoad Call AttributeLoad AttributeLoad NameLoad attr attr keyword Num keyword Num keyword NameLoad Return Call AttributeLoad NameLoad attr NameLoad decorator_list decorator_list
N/A N/A numpy np sys stderr time time _BaseRegressor N/A object N/A N/A Parent Class Base Regressor

    A base class that is implemented by
    regressor child classes.

     __init__ N/A N/A self print_progress N/A 0 N/A N/A N/A self print_progress print_progress N/A fit N/A N/A self X y init_weights N/A True N/A N/A Learn weight coefficients from training data.

        Parameters
        ----------
        X : {array-like, sparse matrix}, shape = [n_samples, n_features]
            Training vectors, where n_samples is the number of samples and
            n_features is the number of features.
        y : array-like, shape = [n_samples]
            Target values.
        init_weights : bool (default: None)
            Reinitialize weights

        Returns
        -------
        self : object

         N/A N/A N/A N/A init_weights None N/A isinstance init_weights bool N/A N/A N/A AttributeError init_weights must be True, False, or None N/A init_weights N/A N/A N/A self _check_arrays X X y y N/A self N/A predict N/A N/A self X N/A N/A N/A Predict class labels of X.

        Parameters
        ----------
        X : {array-like, sparse matrix}, shape = [n_samples, n_features]
            Training vectors, where n_samples is the number of samples and
            n_features is the number of features.

        Returns
        ----------
        class_labels : array-like, shape = [n_samples]
          Predicted class labels.

         N/A N/A N/A self _check_arrays X N/A N/A N/A self _predict X N/A _predict N/A N/A X y N/A N/A N/A N/A _shuffle N/A N/A self arrays N/A N/A N/A Shuffle arrays in unison. N/A r N/A N/A N/A np random permutation N/A len N/A arrays N/A 0 N/A N/A N/A ary N/A r N/A ary arrays N/A _print_progress N/A N/A self epoch cost time_interval N/A None 10 N/A N/A N/A N/A self print_progress 0 N/A N/A s N/A 
Epoch: %d/%d N/A epoch N/A self epochs N/A cost N/A N/A s N/A  | Cost %.2f cost N/A N/A N/A self print_progress 1 N/A N/A N/A N/A hasattr self ela_str_ N/A N/A N/A self ela_str_ 00:00:00 N/A N/A N/A epoch time_interval N/A N/A ela_sec N/A N/A time N/A self init_time_ N/A N/A self ela_str_ N/A N/A self _to_hhmmss ela_sec N/A s N/A  | Elapsed: %s N/A self ela_str_ N/A N/A N/A self print_progress 2 N/A N/A N/A N/A hasattr self eta_str_ N/A N/A N/A self eta_str_ 00:00:00 N/A N/A N/A epoch time_interval N/A N/A eta_sec N/A N/A N/A ela_sec N/A float epoch N/A self epochs ela_sec N/A N/A self eta_str_ N/A N/A self _to_hhmmss eta_sec N/A s N/A  | ETA: %s N/A self eta_str_ N/A N/A N/A stderr write s N/A N/A N/A stderr flush N/A _to_hhmmss N/A N/A self sec N/A N/A N/A N/A m s N/A divmod sec 60 N/A N/A h m N/A divmod m 60 N/A N/A %d:%02d:%02d N/A h m s N/A _check_arrays N/A N/A self X y N/A None N/A N/A N/A isinstance X list N/A N/A N/A ValueError X must be a numpy array N/A N/A N/A N/A len N/A X shape 2 N/A N/A N/A ValueError X must be a 2D array. Try X[:,numpy.newaxis] N/A N/A N/A N/A y None N/A N/A N/A N/A N/A AttributeError N/A N/A N/A N/A N/A len N/A y shape 1 N/A N/A N/A ValueError y must be a 1D array. N/A N/A N/A N/A len y N/A N/A X shape N/A 0 N/A N/A N/A ValueError X and y must contain the same number of samples N/A _init_weights N/A N/A self shape zero_init_weight coef dtype seed N/A False 0.001 float64 None N/A N/A Initialize weight coefficients. N/A seed N/A N/A N/A N/A N/A np random seed seed N/A zero_init_weight N/A N/A w N/A N/A np zeros shape N/A N/A w N/A coef N/A N/A N/A np random normal loc 0.0 scale 1.0 size shape N/A N/A N/A w astype dtype N/A N/A