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object fitctree predictorimportance function  (MathWorks Inc)


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    MathWorks Inc object fitctree predictorimportance function
    Object Fitctree Predictorimportance Function, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/predictorimportance+function/ppr0677648-96-12-6
    Average 90 stars, based on 1 article reviews
    object fitctree predictorimportance function - by Bioz Stars, 2026-11
    90/100 stars

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    Article Title: A machine learning model based on readers’ characteristics to predict their performances in reading screening mammograms
    Article Snippet: Using MATLAB’s predictorImportance function, the three most important features in the AUC model were number of years since certification, position, and number of cases per week while the three features for the lesion sensitivity were number of cases per week, number of hours per week, and number of years reading mammograms.

    Article Title: Classifying Epileptic Seizure Events from EEG Signals by a Lightweight Machine Learning Model
    Article Snippet: This was performed using the existing MATLAB object fitctree, more specifically, the predictorImportance() function from within the object [7].

    Article Title: Machine learning-based prediction of anatomical outcome after idiopathic macular hole surgery
    Article Snippet: It estimates the importance of each predictor by using the predictorImportance function in MATLAB.

    Article Title: Determination of the most significant rubber components influencing the hardness of natural rubber (NR) using various statistical methods
    Article Snippet: Based on the classification decision tree grow we can applied the predictorImportance function of MATLAB to estimate the importance values of predictor variables for the tree.

    Article Title: Adaptive Machine Learning for Electronic Nose-Based Forensic VOC Classification.
    Article Snippet: To interpret the Optimizable Ensemble model’s predictor contributions, we conducted a feature importance analysis using MATLAB’s predictorImportance function.



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