Pytorch regression _1.1_[WorldHappinessReport]
290420201753. Tworzenie małych prototypów o pełnej zdolności bojowej Cele: 1. podstawić prawdziwy plik danych 2. przeliczyć zapamiętać model odpalić model 3. zweryfikowac model czy liczy […]
Review of models based on gradient falling: XGBoost, LightGBM, CatBoost
240120202201 In [67]: # Classification Assessment def Classification_Assessment(model ,Xtrain, ytrain, Xtest, ytest): import numpy as np import matplotlib.pyplot as plt from sklearn import metrics from sklearn.metrics […]
Kilka prostych przykładów z programowanie objektowe w Python
240420202112 Koty¶ In [1]: class kolor_kota(object): def __init__(self, imię, kolor): self.imię = imię self.kolor = kolor In [2]: nk1 = kolor_kota(‘Kremówka’, ‘ruda’) nk2 = kolor_kota(‘Helen’, ‘biało-szary’) In [3]: […]
Perfect Plots Bubble Plot [definitions] 100420201321
Perfect Plots: Bubble Plot [definitions] In [1]: import pandas as pd import matplotlib.pyplot as plt import numpy as np Autos¶ Source of data: https://datahub.io/machine-learning/autos In [2]: df2= […]
Perfect Plots_ Matrix of corelation
281120190000 Source of data: https://archive.ics.uci.edu/ml/datasets/combined+cycle+power+plant Combined Cycle Power Plant Data Set¶ Data Set Information:¶ The dataset contains 9568 data points collected from a Combined Cycle […]
Perfect plot Joyplot
100420201543 In [1]: import joypy import pandas as pd import matplotlib.pyplot as plt Car market analysis¶ Source of data: https://github.com/selva86/datasets/blob/master/mpg_ggplot2.csv GSuite Text and Background Palette: […]
Interpretation of SHAP charts for the Titanic case (Feature Selection Techniques)
090420202257 https://github.com/slundberg/shap https://slundberg.github.io/shap/notebooks/NHANES%20I%20Survival%20Model.html In [1]: import pandas as pd df = pd.read_csv(‘/home/wojciech/Pulpit/1/tit_train.csv’, na_values=”-1″) df.head(2) Out[1]: Unnamed: 0 PassengerId Survived Pclass Name Sex Age SibSp […]
Homemade loop to search for the best functions for the regression model (Feature Selection Techniques)
090420201150 In [1]: import pandas as pd df = pd.read_csv(‘/home/wojciech/Pulpit/1/tit_train.csv’, na_values=”-1″) df.head(2) Out[1]: Unnamed: 0 PassengerId Survived Pclass Name Sex Age SibSp Parch Ticket Fare […]
How to calculate the probability of survival of the Titanic catastrophe_080420201050
080420201050 practical use: predict_proba In [1]: import numpy as np import pandas as pd from sklearn.model_selection import train_test_split from sklearn.ensemble import RandomForestClassifier In [2]: from catboost.datasets import […]
(B29) CatBoostClassifier #2
060420202152 https://github.com/catboost/tutorials/blob/master/python_tutorial.ipynb CatBoostClassifier sam koduje sobie zmienne tekstowe kategoryczne na zmienne kategoryczne wyrażone numerycznie. Jeżeli sami przeprowadzimy codowanie i zakodujemy zmienne kategoryczne na format cyfrowy, […]
CatBoost Step 1. CatBoostClassifier (cat_features)
030420200928 In [1]: ## colorful prints def black(text): print(’33[30m’, text, ’33[0m’, sep=”) def red(text): print(’33[31m’, text, ’33[0m’, sep=”) def green(text): print(’33[32m’, text, ’33[0m’, sep=”) def […]
Feature Selection Techniques [categorical result] – Step Forward Selection
010420201017 Forward selection is an iterative method in which we start with no function in the model. In each iteration, we add a function that […]
Feature Selection Techniques – Recursive Feature Elimination and cross-validated selection (RFECV)
300320202100 RFECV differs from Recursive Feature Elimination (RFE) in the function selection process in that it indicates the OPTIMAL NUMBER OF VARIABLES and not the […]
Feature Selection Techniques – Embedded Method (Lasso)
300320202027 Embedded methods are iterative in a sense that takes care of each iteration of the model training process and carefully extract those features which […]
Feature Selection Techniques – Recursive Feature Elimination (RFE)
300320201719 It is a greedy optimization algorithm which aims to find the best performing feature subset. It repeatedly creates models and keeps aside the best […]