thesfinox

# -*- coding: utf-8 -*-
"""
Denoise using wavelet transformations.

@author: Riccardo Finotello <riccardo.finotello@gmail.com>
"""
from typing import Optional

import numpy as np
import pywt

thesfinox

import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
import statsmodels.formula.api as sm

sns.set_theme()

#######################
#                     #

thesfinox

# Marchenko-Pastur distribution
# see https://en.wikipedia.org/wiki/Marchenko%E2%80%93Pastur_distribution
def marchenko_pastur(x, c, var=1.0):
    '''
    Marchenko-Pastur PDF.
    
    Arguments:
    
        x:   independent variable,
        c:   phase transition parameter,

thesfinox

from sklearn.ensemble import GradientBoostingRegressor
from joblib           import Parallel, delayed

# create a list of parameters
params = [{'learning_rate': 0.01, 'subsample': 0.8, 'n_estimators': 100},
          {'learning_rate': 0.03, 'subsample': 0.5, 'n_estimators': 300},
          {'learning_rate': 0.001, 'subsample': 0.9, 'n_estimators': 50},
          {'learning_rate': 0.003, 'subsample': 0.1, 'n_estimators': 10},
         ]