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variance in machine learning

Json Bourne answered on December 15, 2021 Popularity 9/10 Helpfulness 2/10

answer variance in machine learning

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variance in machine learning

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from mlxtend.evaluate import bias_variance_decomp
from sklearn.tree import DecisionTreeClassifier
from mlxtend.data import iris_data
from sklearn.model_selection import train_test_split
# Get Data Set
X, y = iris_data()
X_train_ds, X_test_ds, y_train_ds, y_test_ds = train_test_split(X, y,
test_size=0.3,
random_state=123,
shuffle=True,
stratify=y)
# Define Algorithm 
tree = DecisionTreeClassifier(random_state=123)
# Get Bias and Variance - bias_variance_decomp function
avg_expected_loss, avg_bias, avg_var = bias_variance_decomp(
tree, X_train_ds, y_train_ds, X_test_ds, y_test_ds, 
loss='0-1_loss',
random_seed=123,
num_rounds=1000)
# Display Bias and Variance
print(f'Average Expected Loss: {round(avg_expected_loss, 4)}n')
print(f'Average Bias: {round(avg_bias, 4)}')
print(f'Average Variance: {round(avg_var, 4)}')

Popularity 9/10 Helpfulness 2/10 Language python

Source: www.bmc.com

Tags: machine-learning python variance

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Contributed on Jun 17 2022

Json Bourne

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variance in Machine learning determines the amount of bias a machine can accept when receiving new values in datasets.

Popularity 10/10 Helpfulness 2/10 Language python

Source: Grepper

Tags: machine-learning mach

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Contributed on Dec 15 2021

Cheerful Capuchin

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variance in machine learning

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