Logistic Regression multiclass didn't recognize ?

It sounds like you're referring to a situation where logistic regression didn't recognize a multiclass problem. By default, logistic regression is designed for binary classification (i.e., distinguishing between two classes). When applied to multiclass classification problems, it needs to be adapted.

Logistic Regression

Here are a few common ways to handle multiclass classification with logistic regression:

1. One-vs-Rest (OvR)

In this approach, the logistic regression model is trained separately for each class. Each model treats one class as the "positive" class and all other classes as the "negative" class. The class with the highest predicted probability is selected for each input sample.

• Pros: Simple to implement.

• Cons: For many classes, training can become slow.

2. Multinomial Logistic Regression

Multinomial logistic regression is a generalization of binary logistic regression to multiclass problems. Instead of learning separate models for each class, it fits a single model that predicts the probability of each class directly.

• Pros: Can give better performance than OvR.

• Cons: More complex and computationally expensive.

3. One-vs-One (OvO)

In this strategy, a classifier is trained for every possible pair of classes. This means if you have kkk classes, you train k(k−1)/2k(k-1)/2k(k−1)/2 classifiers. When predicting a class, a voting scheme is used across all classifiers.

• Pros: Can be useful when classes are highly imbalanced.

• Cons: High computational cost due to the number of classifiers required.

Possible Issues You Encountered:

1. Model not recognizing multiclass problem: Ensure that your logistic regression algorithm supports multiclass classification, or explicitly specify a strategy like OvR or multinomial.

2. Wrong library or parameter settings: If you're using a library like scikit-learn, you need to ensure you’ve set the multi_class parameter to multinomial or ovr. Example:

from sklearn.linear_model import LogisticRegression
model = LogisticRegression(multi_class='multinomial', solver='lbfgs')

Let me know if this is what you're facing or if you need more specific help!