Breaking News: Grepper is joining You.com. Read the official announcement!

logistic regression algorithm

Add Answer

josh.ipynb answered on May 23, 2020 Popularity 10/10 Helpfulness 3/10

answer logistic regression algorithm

related logistic regression algorithm in python

related logistic regression is a classification algorithm

related logistic regression algorithm in python

related logistic regression

related python logistic regression

logistic regression algorithm

Comment

# Import the necessary modules
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import confusion_matrix, classification_report

# Create training and test sets
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.4, random_state=42)

# Create the classifier: logreg
logreg = LogisticRegression()

# Fit the classifier to the training data
logreg.fit(X_train, y_train)

# Predict the labels of the test set: y_pred
y_pred = logreg.predict(X_test)

# Compute and print the confusion matrix and classification report
print(confusion_matrix(y_test, y_pred))
print(classification_report(y_test, y_pred))

Popularity 10/10 Helpfulness 3/10 Language python

Source: campus.datacamp.com

Tags: algorithm logistic-regression python

Link to this answer
Share Copy Link

Contributed on Jun 07 2022

josh.ipynb

0 Answers Avg Quality 2/10

Closely Related Answers

logistic regression algorithm in python

Comment

# import the class
from sklearn.linear_model import LogisticRegression

# instantiate the model (using the default parameters)
logreg = LogisticRegression()

# fit the model with data
logreg.fit(X_train,y_train)

#
y_pred=logreg.predict(X_test)

Popularity 10/10 Helpfulness 5/10 Language python

Source: www.datacamp.com

Tags: algorithm algo

Link to this answer
Share Copy Link

Contributed on May 23 2020

Wide-eyed Whale

0 Answers Avg Quality 2/10

logistic regression is a classification algorithm

Comment

logistic regression is a classification algorithm

Popularity 10/10 Helpfulness 2/10 Language javascript

Source: Grepper

Tags: algorithm algo

Link to this answer
Share Copy Link

Contributed on Jan 07 2023

Itchy Ibex

0 Answers Avg Quality 2/10

logistic regression algorithm in python

Comment

# import the metrics class
from sklearn import metrics
cnf_matrix = metrics.confusion_matrix(y_test, y_pred)
cnf_matrix

Popularity 10/10 Helpfulness 2/10 Language python

Source: www.datacamp.com

Tags: algorithm algo

Link to this answer
Share Copy Link

Contributed on May 23 2020

Wide-eyed Whale

0 Answers Avg Quality 2/10

logistic regression

Comment

- It is a classification problem
- It is called regression because it calculates continuous value (sigmoid / likelihood /probability) 
- It compares threshold value with probability to reach conclusion 
- It works well for data with 2 class that is linearly separable by a line (decision boundary)
- For multiple classes, use softmax
- Logistic regression only calculates probability of positive (target) class only. subtracting from 1 will give us probability of negative class
- Training process:
    1. Initializes theta (co-efficients) with random values
    2. Calculate sigmoid (probability) of output for a case
    3. compare this probability with actual output and record this difference as error
    4. Calculate this error for all training cases. Total error is the cost of the model (known as cost function. eg: MSE)
    5. Change theta in such a way that it reduces total cost (optimization algorithm like gradient descent)
    6. Iterate from step 2 until the model is satisfactory enough with low cost.

Popularity 10/10 Helpfulness 2/10 Language whatever

Source: Grepper

Tags: logistic-regression logi

Link to this answer
Share Copy Link

Contributed on Feb 13 2023

Innocent Iguana

0 Answers Avg Quality 2/10

python logistic regression

Comment

from statsmodels.formula.api import logit
model = logit("target ~ x_var", data=df).fit()
print(model.params)
# Visualize logistic model
sns.regplot(x="x_var", y="target", data=df, ci=None, logistic=True)
X_test = pd.DataFrame({"x_var": np.arange(-1, 6.25, 0.25)})
y_pred_prob = model.predict(X_test)
y_pred = np.round(y_pred_prob)
# Odds ratio : p/(1-p) or probability of something happenning over not happening
odds_ratio = y_pred_prob / (1- y_pred_prob)
# Visualize odds ratio / log odds ratio
sns.lineplot(x="x_var", y="odds_ratio", data=df)
plt.axhline(y=1, linestyle="dotted")
plt.yscale("log") # If you want to make the curve into linear make y : np.log(odds_ratio)
plt.show()
# Confusion matrix
conf_matrix = model.pred_table()
TN = conf_matrix[0,0]
TP = conf_matrix[1,1]
FN = conf_matrix[1,0]
FP = conf_matrix[0,1]
# Visualize confusion matrix
from statsmodels.graphics.mosaicplot import mosaic
mosaic(conf_matrix)

Popularity 10/10 Helpfulness 2/10 Language python

Source: Grepper

Tags: logistic-regression logi

Link to this answer
Share Copy Link

Contributed on Dec 23 2023

Innocent Iguana

0 Answers Avg Quality 2/10

logistic regression algorithm

Contents

More Related Answers

logistic regression algorithm

Closely Related Answers

logistic regression algorithm in python

logistic regression is a classification algorithm

logistic regression algorithm in python

logistic regression

python logistic regression

Grepper

Documentation

Social

Legal

Contact

Oops, You will need to install Grepper and log-in to perform this action.