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view all learning resourcesHi. I have been working with the Equity file (JMP Database) on JMP Pro 18 to build a Bootstrap Forest with a Categorical Response (BAD). I have followed the instruction as given on https://www.jmp.com/support/help/en/17.1/?os=win&source=application#page/jmp/example-of-bootstrap-forest-with-a-categorical-response.shtml#However, the report does not include the confusion matrix. Can anyone suggest m...
Hi, I was able to identify consecutive values on a column "Data" (Refer to " sequence roll" column). However i need to generate a column (refer to Expected Result column) to sum up the number of consecutive values.Any help or advice will be appreciate. Thank you " sequence roll" columnIf( :Item == Lag( :Item, 1 ),
If( Dif( :Data, 1 ) == 1,
Dif( :Data, 1 ), .
), .
)
如果试验自变量为分类变量,响应为连续变量,是否可以使用正交设计进行筛选?例如:氨基酸作为一个自变量,其中有20种不同的氨基酸,维生素作为一个自变量,其中有8种,筛选氨基酸和维生素的最佳组合,可否使用正交设计,谢谢!
Hello, I'm looking for a way to test a different LDA strategy than the standard One-off (or hand-out) method when trying to predict a categorical repsonse with multiple classes. I'm particullarilly interested in the One-Versus-Rest (OVR) (also referred to as One-Versus-All or OVA) and the One-Versus-One (OVO) startegies. Thanks in advance!
如果试验自变量为分类变量,响应为连续变量,是否可以使用正交设计进行筛选?例如:氨基酸作为一个自变量,其中有20种不同的氨基酸,维生素作为一个自变量,其中有8种,筛选氨基酸和维生素的最佳组合,可否使用正交设计,谢谢!
Hello, I'm looking for a way to test a different LDA strategy than the standard One-off (or hand-out) method when trying to predict a categorical repsonse with multiple classes. I'm particullarilly interested in the One-Versus-Rest (OVR) (also referred to as One-Versus-All or OVA) and the One-Versus-One (OVO) startegies. Thanks in advance!
Hello, I fit the negative log-likelihood function for a Poisson distribution (green highlighted column in the attached .jmp file) to my observed data and get the mean estimates for 10 unknown parameters (screenshot below). My problem is bootstrapping these 10 parameters using the parametric method. The one-button "bootstrap" function in jmp (after right-click on the column "Estimate") gives me 1...
Hi everyone, I'm attempting to create a forest plot figure based on multiple logistic regression models. I have 9 independent variables and four IQ outcomes, VCI, POI, PSI and Full IQ. Each outcome has three thresholds <70 vs >=90, 70-79 vs >=90 and 80-89 vs >=90.All was fine but I detected some bugs when drawing the lines in the plot. For example, in females for Perceptual organization index (POI...
Hello Community!Attached is the script "Hogi chart calculates risk and probability", an excellent work by HOGI ... which calculates the risks and probabilities of occurrence of an input or multiple inputs (x), of an output or multiple outputs (Y) or their combination in a table. For example:Would it be possible to expand the capacity of the script to make a sensitivity analysis of the inputs (x) o...
Hi, I have a multinomial logistic regression of 3 classes: 0, 1, and 2 and have associated individual models (via Fit Y by X) for N parameters. I am now looking into a sensitivity like study in which each parameter is assumed at certain levels (e.g. at min, max etc..). I have probabilities computed at each such parameter level. I like to rank order probability change in each class (0, 1 and 2) du...
Dear JMP community,I am presented with a problem of building a model using over-dispersed zero-inflated count data. I hope you can help me with this.I have attached both training and validation datasets to this post. My objective is to build my model on the training dataset and validate it using the validation dataset. I have not worked with such count data before and therefore do not know validat...
Hello,I'm trying to reproduce the results obtained on JMP with the "Neural" model by adding nested cross-validation, which is not possible on the software. However, the architecture is very unclear and I can't understand the calculations performed by the model. I don't have access to certain information such as batch size, optimizer used, loss, learning rate (except the one for the boosting), and ...
Why doesn't a large and powerful program like JMPPRO contain hybrid models in time series such as the ARIMA-ANN model, ARMAX model, and others?
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