How to test and import a model form computer to test accuracy using Sklearn library - Printable Version +- Python Forum (https://python-forum.io) +-- Forum: Python Coding (https://python-forum.io/forum-7.html) +--- Forum: General Coding Help (https://python-forum.io/forum-8.html) +--- Thread: How to test and import a model form computer to test accuracy using Sklearn library (/thread-34107.html) |
How to test and import a model form computer to test accuracy using Sklearn library - Anldra12 - Jun-27-2021 Which types of data model we can test like which format don't know i have some model i want to check the accuracy using logistic regression for the accuracy I download some models where my task to predict feathers for the same model using Secure KNN algorithm Looks at the below codes # read in the iris data from sklearn.datasets import load_iris iris = load_iris() # create X (features) and y (response) X = iris.data y = iris.target # 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, y) # predict the response values for the observations in X logreg.predict(X) # store the predicted response values y_pred = logreg.predict(X) # check how many predictions were generated len(y_pred) RE: How to test and import a model form computer to test accuracy using Sklearn library - jefsummers - Jun-27-2021 score(x,y) See Logistic Regression documentation RE: How to test and import a model form computer to test accuracy using Sklearn library - Anldra12 - Jun-27-2021 @jefsummers thanks not just for prediction read post how we apply others types of data set RE: How to test and import a model form computer to test accuracy using Sklearn library - jefsummers - Jun-28-2021 I can tell English is not your first language, but you are way better at English than I would be at your native language. I don't quite understand the question however. Let me try to break it down, maybe by luck I will hit on what you are looking for - Two types of data - continuous and categorical Four types of predictions, then - Continuous -> Continuous - use linear regression (or similar) Continuous -> Categorical - use logistic regression Categorical -> Continuous - use ANOVA (analysis of variance) Categorical -> Categorical - use chi square If this did not help please rephrase the question. RE: How to test and import a model form computer to test accuracy using Sklearn library - Anldra12 - Jun-29-2021 @jefsummers quite simple let suppose we want to check others types of data model instead of Iris data How we import this model for the predictions for example look at the codes as follow This an iris data set but replace this model from sklearn.datasets import load_iris iris = load_iris()I replace iris to other model how this will happen just for an example from sklearn.datasets import Cancer_df Cancer = load_ Cancer_df()After that we apply your proposed model Two types of data - continuous and categorical Four types of predictions, then - Continuous -> Continuous - use linear regression (or similar) Continuous -> Categorical - use logistic regression Categorical -> Continuous - use ANOVA (analysis of variance) Categorical -> Categorical - use chi square RE: How to test and import a model form computer to test accuracy using Sklearn library - jefsummers - Jul-01-2021 It depends on how the model was created and stored. Here is the documentation from sklearn regarding saving and loading models https://scikit-learn.org/stable/modules/model_persistence.html I recommend the interoperable formats mentioned at the bottom of the article rather than pickle, for the concerns that pickle is unique to Python and that arbitrary code execution is possible. RE: How to test and import a model form computer to test accuracy using Sklearn library - Anldra12 - Jul-03-2021 @jefsummers yes i will look at this |