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  • Machine Learning - Save Variable(s) - Probabilities of Each Response (category Create Machine Learning)
    assigns probabilities for observations not in the estimation sample. includeWeb('QScript R Output Functions'); saveVariables('Probabilities', 'Machine Learning
    1 KB (73 words) - 00:57, 21 August 2023
  • Machine Learning - Ensemble of Models (category Create Machine Learning) (section SAVE VARIABLE(S))
    may also be provided. Machine Learning - Save Variable(s) - Predicted Values and Machine Learning - Save Variable(s) - Probabilities of Each Response may
    17 KB (1,559 words) - 05:23, 20 October 2023
  • Machine Learning - Linear Discriminant Analysis (category Create Machine Learning) (section SAVE VARIABLE(S))
    prior probabilities used in computing the probabilities of group membership of the Outcome (Machine Learning - Save Variable(s) - Probabilities of Each
    23 KB (2,444 words) - 05:23, 20 October 2023
  • Machine Learning - Deep Learning (category Create Machine Learning) (section SAVE VARIABLE(S))
    the Outcome. Algorithm The machine learning algorithm. Defaults to Deep Learning but may be changed to other machine learning methods. Output Accuracy When
    20 KB (2,045 words) - 05:23, 20 October 2023
  • Machine Learning - Classification And Regression Trees (CART) (category Create Machine Learning) (section SAVE VARIABLE(S))
    from the model. Algorithm The machine learning algorithm. Defaults to CART but may be changed to other machine learning methods. Output How the tree should
    20 KB (2,119 words) - 05:23, 20 October 2023
  • Regression - Linear Regression (section SAVE VARIABLE(S))
    Predictors The variable(s) to predict the outcome. Algorithm The fitting algorithm. Defaults to Regression but may be changed to other machine learning methods
    18 KB (3,629 words) - 05:23, 20 October 2023
  • Machine Learning - Random Forest (category Create Machine Learning) (section SAVE VARIABLE(S))
    the outcome. Algorithm The machine learning algorithm. Defaults to Random Forest but may be changed to other machine learning methods. Output Importance
    23 KB (2,358 words) - 05:23, 20 October 2023
  • Machine Learning - Gradient Boosting (category Create Machine Learning) (section SAVE VARIABLE(S))
    either a numeric or categorical variable. Predictors The variable(s) to predict the outcome. Algorithm The machine learning algorithm. Defaults to Gradient
    21 KB (2,266 words) - 05:23, 20 October 2023
  • Machine Learning - Support Vector Machine (category Create Machine Learning) (section SAVE VARIABLE(S))
    outcome. Algorithm The machine learning algorithm. Defaults to Support Vector Machine but may be changed to other machine learning methods. Output Accuracy
    27 KB (3,019 words) - 05:23, 20 October 2023
  • Release Notes
    number of levels and variables per case to save for the Text Analysis - Save Variable(s) - Categories and Text Analysis - Save Variable(s) - First Category
    84 KB (10,645 words) - 06:37, 2 April 2024
  • Regression - Ordered Logit (section SAVE VARIABLE(S))
    Predictors The variable(s) to predict the outcome. Algorithm The fitting algorithm. Defaults to Regression but may be changed to other machine learning methods
    19 KB (3,646 words) - 05:23, 20 October 2023
  • Regression - Binary Logit (section SAVE VARIABLE(S))
    Predictors The variable(s) to predict the outcome. Algorithm The fitting algorithm. Defaults to Regression but may be changed to other machine learning methods
    20 KB (3,631 words) - 05:23, 20 October 2023
  • Regression - Poisson Regression (section SAVE VARIABLE(S))
    Predictors The variable(s) to predict the outcome. Algorithm The fitting algorithm. Defaults to Regression but may be changed to other machine learning methods
    19 KB (3,781 words) - 05:23, 20 October 2023
  • Regression - Multinomial Logit (section SAVE VARIABLE(S))
    Predictors The variable(s) to predict the outcome. Algorithm The fitting algorithm. Defaults to Regression but may be changed to other machine learning methods
    20 KB (3,811 words) - 05:23, 20 October 2023
  • Regression - Generalized Linear Model (section SAVE VARIABLE(S))
    the model you want to use Outcome The variable to be predicted by the predictor variables. Predictors The variable(s) to predict the outcome. Algorithm The
    19 KB (3,813 words) - 05:23, 20 October 2023
  • Regression - NBD Regression (section SAVE VARIABLE(S))
    Predictors The variable(s) to predict the outcome. Algorithm The fitting algorithm. Defaults to Regression but may be changed to other machine learning methods
    19 KB (3,754 words) - 05:23, 20 October 2023
  • Regression - Quasi-Poisson Regression (section SAVE VARIABLE(S))
    Predictors The variable(s) to predict the outcome. Algorithm The fitting algorithm. Defaults to Regression but may be changed to other machine learning methods
    19 KB (3,733 words) - 05:23, 20 October 2023
  • Regression - Save Variable(s) - Propensity Weight
    regression or Machine Learning ' + 'classification model with a binary outcome variable)'; let question_type = 'Number'; let is_weight = true; let variable_name
    2 KB (530 words) - 00:51, 8 May 2023
  • Regression - Driver Analysis (section SAVE VARIABLE(S))
    Interaction Optional variable to test for interaction with other variables in the model. The interaction variable is treated as a categorical variable. Coefficients
    23 KB (4,336 words) - 05:23, 20 October 2023
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