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Latest Discussions

• How do I fix base level for indicator function parameterization

  If my data has 1's and 0's in a column for a X and I am running a regression of Y on X,  how can I force JMP to select one of those as baseline values (instead of JMP picking it based on its internal rule) in creating indicator function parameterization? Thanks

  goutam

  Discussions |

  Jul 21, 2020 7:53 AM

  1575 views | 1 replies

• Proportion between size of training and test data set

  Hi, I have a relatively small data set with 95 observations/records and about 70 variables for each record. The goal is to detect which variables influence the response and find the optimal settings of these variables. Because of the small number of observations I decided to divide data into only two categories, training and test data set (omitting the validation data set). My strategy is to apply...

  StefanC

  Discussions |

  Jul 20, 2020 9:12 AM

  3131 views | 3 replies

• How do use JSL to quickly compare two sets of range columns in order to get the minimum of each column?

  The title is a bit hard to understand. Take this big class as an example:
  1. First, summarize the average values of "height" and "weight" by age.
  2. Then summarize the median of "height" and "weight" by age.
  3. Then compare the mean and median of "height" and take their minimum.
  Finally, compare the mean and median of "body weight" and take their minimum. I'll use the following code and finally loop t...

  lwx228

  Discussions |

  Jun 4, 2020 3:49 PM

  3098 views | 4 replies

• K fold

  Hi!How can I perform a KFold cross-validation with neural networks model by using JMP 15.1?.
  Thanks in advance!

  Marlly_Guarin

  Discussions |

  Jun 2, 2020 10:10 AM

  2000 views | 1 replies

• How do I auto-calculate precision and F1 score for models on imbalanced data?

  I like that JMP's prints a confusion matrix and ROC for the logistic (Generalized) regression, but some important metrics seem to be missing from the results: precision and F1 score. Is there a way to auto-include these in the output? Or, have it be computed as "automatically" as possible when I re-run a new classificaiton model. I am trying to avoid manually recomputing these with each new model....

  Oleg

  Discussions |

  Sep 28, 2017 3:40 PM

  20670 views | 16 replies