Browse 121 Machine Learning questions and answers from learners and industry experts. Find practical fixes, interview prep and step-by-step solutions - or ask your own.
(trainingData, testData) = data.randomSplit([0.7, 0.3]) vecAssembler = VectorAssembler(inputCols=["_1", "_2", "_3", "_4", "_5", "_6", "_7", "_8",…
1 Answer · 1.5K Views · Answered ✓
First we import the data # Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd # Importing the dataset…
2 Answers · 1.8K Views · Answered ✓
Models with either high bias or high variance error components do not produce the ideal fit. Hence, some makeovers are required to do so. In the…
1 Answer · 1.5K Views · Answered ✓
Logistic regression and decision tree are both classification based algorithms but they are very different from each other Logistic regression looks…
1 Answer · 962 Views · Answered ✓
Classification tree: tree(formula = High temperature ~ ., data = summer.train) Variables actually used in tree construction: [1] "Humidity" "Cloudy"…
1 Answer · 1.4K Views · Answered ✓
Siblings Children Gender Survival 1 Y Y F Y 2 N Y M N 3 Y Y M Y 4 N N F N 5 Y N F N
1 Answer · 701 Views · Answered ✓
import numpy as np p = [0.5, 0.2, 0.2, 0.1] q_1 = [0.4, 0.2, 0.2, 0.2] q = [0.4, 0.2, 0.2, 0.2] def cross_entropy(p, q): return…
1 Answer · 1.0K Views · Answered ✓
KNN does not produce wrong results all the time. It largely depends on the dataset. There might be two reasons for this error. The training data…
1 Answer · 1.6K Views · Answered ✓
To calculate the error rate for a decision tree in R, assuming the mean computing error rate on the sample used to fit the model, we can use…
3 Answers · 7.2K Views · Answered ✓
from sklearn.datasets import load_iris from sklearn import tree X, y = load_iris(return_X_y=True) clf = tree.DecisionTreeClassifier() clf =…
1 Answer · 1.4K Views · Answered ✓
from sklearn import tree clf = tree.DecisionTreeClassifier() # [height, weight, shoe_size] X = [[181, 80, 44], [177, 70, 43], [160, 60, 38], [154,…
1 Answer · 1.5K Views · Answered ✓
import pandas as pd from sklearn.tree import DecisionTreeClassifier data = pd.DataFrame() data['A'] = ['a','a','b','a'] data['B'] = ['b','b','a','b']…
1 Answer · 1.1K Views · Answered ✓
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