J. (2012). Using logistic regression modeling to predict sexual recidivism: The Minnesota Sex Offender Screening Tool-3 (MnSOST-3). Sexual Abuse: Journal of Research and Treatment, 24, 350-377.Duwe, G., & Freske, P. (2012). Using logistic regression modeling to predict sexual recidivism:...
Adding a single class weight parameter to the logistic regression function improved the f1 score by 10 per cent. We can see in the confusion matrix that even though the misclassification for class 0 (no heart stroke) has increased, the model can capture class 1 (heart stroke) pretty well. ...
Prediction of mortality in an intensive care unit using logistic regression and a hidden Markov model. Comput. Cardiol. 39, 393–396 (2012). Google Scholar Choi, E. et al. in Advances in Neural Information Processing Systems 29 (eds. Lee, D. D., Sugiyama, M., Luxburg, U. V., ...
Regression analysis (linear, logistic, poisson...) Dashboards (with pivots, slicers and interactive graphs) Forecasting (moving average, exponential smoothing etc.) Excel Solver Slicers Below are the formulas that are covered, Sum/ Sumif Count/ Countif VLOOKUP - HLOOKUP Index Match Text Pattern...
- Logistic Regression: Dealing with binary classification problems and mapping input features to a probability value, commonly used for classification tasks. - Decision Trees: Creating an easy to understand tree-like structure, commonly used to model decision-making processes involving linguistic variables...
Prior to validating the RPM, the study evaluates the performance of the chosen C4.5 algorithm and introduces logistic regression, random forest, and neural network as comparative algorithms, as detailed in Table 2. Table 2 Results of confusion matrix of different algorithms and comparison results of...
Moreover, logistic regression has been used to select features, in combination with the Data Handling Group Method and a smooth group L1/2 regularisation approach. This strategy seeks to remove unnecessary nodes from the inputs of feedforward neural networks, leading to substantial improvements in ...
Monte Carlo techniques are used to calculate liquefaction behavior. Similarly, Chung and David Rogers (2017) used logistic regression, a widely used method to estimate the probability of a liquefaction event. In particular, they recommend using the following formula in Eq.1to determine this probabili...
Logistic regression showed that presence of foveal pathology was a significant factor in model performance OR (95% CI): 0.36 (0.19, 0.70) p = 0.0022. Sex was not associated with presence of foveal pathology (p = 0.94). This suggests that the fovea may be a salient region of ...
9 suggested a SDP model for Just-in-Time (JIT) defect prediction. Their approach uses a deep belief network (DBN) to extract an informative set of features from a given set of basic change metrics. Subsequently, it utilizes logistic regression to train a classifier model based on the ...