**38**
results

**38**
results

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###### Predict sales for a retail store with linear regression

- Prepare train and test data - Treat missing value - Finding correlation - Train a Linear Regression model - Apply trained regre…shubham769 > Public > Predict sales amount with linear regression > Predict sales for a retail store with linear regression2 - Go to itemWorkflow
###### Linear Regression to calculate Price of a Lego set

The workflow trains a Linear Regression model to predict the price of a Lego set based on it's various features. It includes the …swantikag > Public > LinearRegression-LegoSet > LinearRegressionModel > LinearRegression-LegoSet1 - Go to itemExercise 4 for KNIME User Training - Training a Decision Tree to predict a nominal target column - Evaluate the model performance…mprof9 > Public > L1-DS KNIME Analytics Platform for Data Scientists - Basics > exercises > 04. Data Mining0
- Go to itemExercise 4 for KNIME User Training - Training a Decision Tree to predict a nominal target column - Evaluate the model performance…mjott > Public > L1-DS KNIME Analytics Platform for Data Scientists - Basics > solutions > 04. Data Mining - solution0
- Go to itemWorkflow
###### Linear Regression Example - Ames Housing Data

A linear regression model is trained to predict prices of houses in Ames, Iowa, USA. A number of numerical features are included …alinebessa > Courses and Workshops > Norbert and Michael - Workshop > HousePrice > Linear_Regression0 - Go to itemThis workflow is the Knime implementation of the codes in the article "A Complete Guide To Regressional Analysis Using Python by …ehsant > Public > Regression0
- Go to itemThis workflow shows an example of time series analysis using the pre-packaged metanodes Time Series Auto-Prediction Training and …rs1 > Public > KNIMEPress > KNIME_Advanced_Luck_4.5_2022011 > AdvancedLuck > Chapter4 > 3. Time_Series_no_flowvars0
- Go to itemExercise 4 for KNIME User Training - Training a Decision Tree to predict a nominal target column - Evaluate the model performance…knime > Education > Courses > L1-DS KNIME Analytics Platform for Data Scientists - Basics > exercises > 04. Data Mining0
- Go to itemThis workflow shows an example of time series analysis using the pre-packaged metanodes Time Series Auto-Prediction Training and …rs1 > Public > KNIMEPress > KNIME_Advanced_Luck_4.4_20210803 > AdvancedLuck > Chapter5 > 3. Time_Series_flowvars0
- Go to itemIntroduction to Machine Learning Algorithms course - Session 2 Solution to exercise 1 - Partition data into training and test set…hayasaka > L4-ML-2Hrs-2021-07 > Solutions > 01_Linear_Regression_solution0
- Go to itemethan_74 > Public > L1-DS KNIME Analytics Platform for Data Scientists - Basics > solutions > 04. Data Mining - solution0
- Go to itemThis workflow shows an example of time series analysis using the pre-packaged metanodes Time Series Auto-Prediction Training and …rs1 > Public > KNIMEPress > KNIME_Advanced_Luck_4.6_20220810 > AdvancedLuck > Chapter4 > 3. Time_Series_no_flowvars0
- Go to itemrs1 > Public > KNIMEPress > KNIME_Advanced_Luck_4.6_20220810 > AdvancedLuck > Chapter5 > 3. Time_Series_flowvars0
- Go to itempau22nanda > Public > L1-DS KNIME Analytics Platform for Data Scientists - Basics > solutions > 04. Data Mining - solution0
- Go to itemIntroduction to Machine Learning Algorithms course - Session 2 Exercise 1 - Partition data into train and test set - Train a line…hayasaka > L4-ML-2Hrs-2021-07 > Exercises > 01_Linear_Regression0
- Go to itemjeany > Public > KNIMEPress > KNIME_Advanced_Luck_4.1_20200525 > AdvancedLuck > Chapter5 > 3. Time_Series_flowvars0
- Go to itemmanpato > Public > L1-DS KNIME Analytics Platform for Data Scientists - Basics > exercises > 04. Data Mining0
- Go to itemkzhqtt > Public > L1-DS KNIME Analytics Platform for Data Scientists - Basics > exercises > 04. Data Mining0
- Go to itemkzhqtt > Public > L1-DS KNIME Analytics Platform for Data Scientists - Basics > solutions > 04. Data Mining - solution0
- Go to itemrs1 > Public > KNIMEPress > KNIME_Advanced_Luck_4.5_2022011 > AdvancedLuck > Chapter5 > 3. Time_Series_flowvars0

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