STIPS Module 7: Predictive Modeling and Text Mining
Statistical Thinking for Industrial Problem Solving (STIPS) is a free, online course available to anyone interested in building practical skills in using data to solve problems better. The ...
Statistical Thinking for Industrial Problem Solving (STIPS) is a free, online course available to anyone interested in building practical skills in using data to solve problems better. The ...
The models you use depend on your data, the questions you are trying to answer and the problems you want to solve. See how to decide by working through case studies that illustrate how to identify, f...
These hands-on activities allow you to practice predictive modeling using JMP. The data files for the activity are in the zip file attached to this post. Extract the data in Predictive Modeling Hands...
Sampling points from curved data typically is not the most accurate way to create a predictive model. In many cases the sampled points miss variability that could impact outcome. This demo uses...
The models you use depend on your goals, what you are trying to do and the questions you are trying to answer. See SEs work through some case studies that give examples of how identify the JMP models...
See how to screen models to find the most appropriate, best model for your needs and the goals of your study or experiment. Model Screening, introduced in JMP Pro 16, streamlines your workflow ...
See how to: Understand the benefits of Generalized Regression (Penalized Regression) Use JMP Pro lasso and elastic net shrinkage techniques to reduce prediction variance, handle ...
Sampling points from curved data typically is not the most accurate way to create a predictive model. In many cases the sampled points miss variability that could impact outcome. This demo uses...
These videos provide JMP essentials for new users and those who want a refresher. Overviews What’s New in JMP 17 Automating Your Analysis Workflow JMP Tips and Tr...
Use JMP Pro to build a sustainable empirical model based on spectral data/wavelengths. See how to: Examine data using Graph Builder to get idea of what different spectra l...
Observational data lends itself to analysis useful for large data sets, data that probably do not exhibit orthogonality and situations where we are interested in prediction rather than interpret...
Learn about: Two approaches Global - more stable, less flexible Local - less stable, more flexible Preventing overfitting Linear Regression, Stepwise Regression, Genera...
See how the new Model Screening capabilities introduced with JMP Pro 16 let you run multiple predictive modeling platforms from one launch window and assemble summaries and compare fits from the...
...easurement system study example NOTE: Q&A is included at times 37:52 and 53:21. Resources: Overview and random coefficients models blog post Repeated measures and panel data m...
See how to: Understand the manufacturing yield example used in the demo Find patterns Use Distribution to examine the relationship between variables and between variab...
JMP 16 ist vollgepackt mit neuen und hilfreichen Verbesserung der vorhandenen Funktionen. Neben einigen Highlights wie Aktions-Aufzeichnung und Log-Modus und Modell-Screening lernen Sie in diesem Mas...
Every new version of JMP and JMP Pro adds considerable functionality to what is an already very powerful tool, and v.16 is no exception. It would be impossible to show all of these additions in...
Learn more in our free online course: Statistical Thinking for Industrial Problem Solving In this video, we show how to fit a penalized regression model using generalized regression in JM...
See how to: Quantify positive or negative sentiment in unstructured text data Understand basics of Lexical Sentiment Analysis Scores sentiment from individual words in each doc when no exter...
See how to: Understand a neural network as a function of a set of derived inputs, called hidden nodes, that are nonlinear functions of the original inputs Interpret Neural Ne...
Follow the guided examples in these videos to learn how to: Create a Validation Column (JMP Pro) Fit a Multiple Linear Regression Model with Validation Fit a Logistic Model with...
Learn more in our free online course: Statistical Thinking for Industrial Problem Solving In this video, we show how to compare and select predictive models in JMP Pro. We use the data se...
Learn more in our free online course: Statistical Thinking for Industrial Problem Solving In this video, we use the Chemical Manufacturing data. We fit a logistic regression model for the...
Learn more in our free online course: Statistical Thinking for Industrial Problem Solving In this video, we show how to fit linear models using generalized regression. We use the Chemical...
...nalyze, then Predictive Modeling, and then Neural. We start by adding Performance as the Y, Response variable. We select the two groups of predictor variables as X, Factor. Y...
Learn more in our free online course: Statistical Thinking for Industrial Problem Solving In this video, we use the Chemical Manufacturing 2 data. We fit a neural network model f...
...esponse variable and select the two groups of predictors as the X, Factors. This takes us to a specification window. Here, we can specify the number of trees in the forest, the number of terms t...
...elect the two groups of predictors as the X, Factors. There are different options for using model validation in JMP Pro. One method is to specify a holdout portion. For example, we can hold 4...
...he two groups of predictors as the X, Factors. The horizontal line in the partition graph shows the mean of Yield, 82.86. Each point is plotted at its Yield value on the Y axis and is r...