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How to plot both linear regression and Loess curve in Scatter / Bubble chart?
Reference: Retrieve <dataset> -> Show ExampleSet Result -> Visualizations -> Scatter / Bubble Question: In Regression Interpolation, I'd like to be able to view both the Linear line and Loess (smoothing) curve on the same plot. Is there any way to do it without adding a second stacked plot? Stacking seems to be a klugy way…
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Wyh does rapidminer include a variable with a p-value >0,05 in a multiple linear regression?
Hello, I'm doing a multiple linear regression. For my regression I have choosen the M5 prime feature with a min tolerance of 0,05. The final model contains three independent variables. Two of them have a p-value under 0,05 and one is above with a p-value of 0,135 (and t-Stat of 1,543). Two other independent variables have…
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Maximum K
"What
is the maximum k to be used in the optimization?" May I know where can I see this? Thank you! This is about regression analysis
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Gold Price prediction (Prediction or Forecast)
Hello there, I am really new in RM and have been testing out datasets from investing.com which takes XAU/USD pairing as my dataset. The goal is to predict Gold Price prediction movement. In this case, several attributes are given which are Date Price Volume Open Low High Change From this, any possible method to predict…
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If I spend extra money in marketing cost will i get more revenue?
If I spend extra money in marketing cost will i get more revenue? How should I use Linear regression to determine whether the marketing cost will affect the revenue with using rapid miner? Or is there other ways to determine whether the marketing cost will affect the revenue with using rapid miner? Data from excel is…
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Setting the whole matrix dataset as a label
Let's say you have two-time series datasets, the first dataset has five explanatory variables, and the other one is a dependent dataset with about 1000 variables, each representing an individual cell. So how do you set the whole dependent dataset as a label for prediction or regression analysis? If not possible, is it…
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m5 Prime
Hi community! Please why is "m5 prime" under feature selection for linear regression when it is a tree model regression itself? I would be glad if you could enlighten me. Thank you. Jer
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how processing data exploration and data preparation with given dataset
I would like to present my first steps about data exploration and data preparation by presantation slides and provided dataset. My issues are: - lack of exploration knowledge (how to see problematic data in order to optimize data quality) - lack of data preparation (creating baseline model "linear regression" with…
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Model building
Hello experts, Sagar here I am a process engineer, Actually right now i am working on the project in process engineering of upgrading of the heat exchanger performance and that heat exchanger is operating on the three different feeds and parameters of the heat exchanger is changing as per the input feed now i have data of…
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What M5, greedy and T-test is meaning
I just try to training model with Linear Regression. I need to know about meaning of M5, greedy and T-test from feature selection. Many thanks for considering my request. :'(
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Linear regression with fixed effects
Hi all, I am currently working on a log-log linear regression model and I need to include some cross sections to the data set to improve the number of observations. I'd like to know if there are some operators in RM that I can use for controlling the cross-sections and determine not only the regression coefficients at a…
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Impute Missing Values with Regression
Hello, I imputed missing values with the K-NN model and tested the performance. The performance is bad that is why I want to try imputing missing values with linear regression and check the performance too. Is that actually possible? If yes, which operators do I have to use? Thanks in advance!
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linear regression nominal data problem
hi everyonei have a problem implementing linear regression on a dataset that has polynomial and numerical data but theproblem is i want to predict Activity which is polynomial values and when i use Nominal to Numerical i still get error thank you all
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i need help in linear regression
Hello everyone i need help in linear Regression im a kind of confused the problem is to: "find out how the number of unsuccessful deliveries per channel will change in the future."and this is how the dataset looks like, the activity and channel attributes are nominal and there are 3 different channel values i used activity…
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Question regarding linear regression model output
Hi RapidMiner Community I tried to make a linear regression model and tried testing the performance of the model through cross validation. The output is a linear function: - 31.472 * Distance in kilometers
+ 34850.105 * WTG Quantity
+ 15042.279 The model performs very well at predicting the cost that I am seeking. However,…
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Linear Regression Graphic
I want to run a linear regression graph with: y1 -126.695 and run against smoker yes/ no and BMI/ age. * A quick note about the smoker/ non-smoker, I am not sure if this can be correct as they are polynomial, how to interpret on a linear regression graph. How do I make a graph using RapidMiner? I see no options…
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How to use an output of one model as an input to another one?
So a noob question here... I have this dataset where I have 10 attributes and two labels, say, Label X and Y. I built individual models for each labels using linear regression and performance was okay but it could be better....but I noticed that the two labels, X and Y are highly correlated and if I use label X as a…
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Linear regression operator - 'greedy' feature selection option
Can someone please help with more details on how the "greedy" feature selection in Linear Regression operator works? In the Optimize Selection operator, the two greedy algorithms (forward selection and backward elimination) are clearly specified. However, in the case of the Linear Regression operator, it is not yet clear…
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linear regression
i am new toRP, can please let me know where I can get a data set + video (for same date) for learning linear regression. thanks!
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Regression issue
Hi everybody I am using linear regression operatore. everything is fine except this issue. I have 15 attributes for linear regression. I use feature selection M5 prime but the final model is weird. I receive "?" instead of numbers in the p-value column. when I remove one attribute form the data, the final result doesn't…
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How can I remove heteroskedasticity from a multiple regression in context of forecasting ?
Hey guys, this is Florian writing, I`m currently facing an issue regarding a multiple regression where I´m pretty much stuck. The context of modelling is a multivariate forecast. Long story short: I have done a residual analysis for the multiple regression, as the the squarred correlation and forecast results itself…
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How to perform oversampling to this
I want to apply oversampling to my data analysis with Rapidminer. I believe my category is not balance Having the NAT-Grade-Remarks as the category, I have VLM, MTM, LM, and AM as value for my category which is the NAT-Grade-Remarks. Now I tried using the Sample operator but nothing is happening it keeps giving me error.…
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Binary Classification - Linear Regression
I am using the mushroom data from UCI. It has two classes p and e. It binary classification problem and all the data is in text form. My data has a column called "class". I set it as a label. Then I performed a "Nominal to Numerical" all the columns since all the data is text. I applied Linear Regression as the model and…
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Predicting ints on titanic dataset.
Excuse my noob level of understanding please, I'm brand new.I am trying to predict mortality on the titanic dataset using cross-validation and linear regression. As you can only use numbers with linear regression, I have converted selected attributes (such as survived) using the 'nominal to numerical' operator. I can see…
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Linear Regression using p-value
I'm trying to do Linear Regression, and I want to create a process which can exclude features using from Training Set by using p-value. So, if a column's p-value is less than 0.05 then remove/ignore that column and repeat the process until we are left with Statistically significant columns for out model. Can someone guide…