Articles by Modeling with R

Ordinal data models

June 8, 2020 | Modeling with R

Introduction Data preparation ordered logistic regression (logit) Ordinal logistic rgeression (probit) CART model Ordinal Random forst model. Continuation Ratio Model Compare models Conclusion Session information Introduction This tutorial aims to explore the most popular models used to predict an ordered response variable. We will use the heart disease data uploaded ...
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Predicting binary response variable with h2o framework

June 2, 2020 | Modeling with R

Introduction data preparation Logistic regression Random forest Introduction H2O is an open source distributed scalable framework used to train machine learning and deep learning models as well as data analysis. It can handle large data sets, with ease of use, by creating a cluster from the available nodes. Fortunately, ...
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Bayesian hyperparameters optimization

May 12, 2020 | Modeling with R

Introduction Bayesian optimization Acquisition functions Data preparation Random forest model The true distribution of the hyperparameters random search bayesian optimization UCB bayesian optimization PI bayesian optimization EI Contrast the results deep learning model Random search Bayesian optimization UCB Bayesian optimization PI Bayesian optimization EI Contrast the results Conclusion Session info ...
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deep learning model for titanic data

May 12, 2020 | Modeling with R

Introducction Data preparation Partition the data & impute the missing values. Convert the data into a numeric matrix. Train the model. Create the model Compile the model Fit the model The model evaluation model tuning Conclusion Introducction Deep learning model belongs to the area of machine learning models which can be ... [Read more...]

Time series with ARIMA and RNN models

May 4, 2020 | Modeling with R

Introduction Data preparation ARIMA model RNN model Reshape the time series Model architecture Model training Prediction results comparison Conclusion Further reading Introduction The classical methods for predicting univariate time series are ARIMA models (under linearity assumption and provided that the non stationarity is of type DS) that use the autocorrelation ...
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Local Snsitivity Hashing Model

April 27, 2020 | Modeling with R

Introduction Data Preparation Prediction Similarity based on distance The similarity based on the number of nearest neighbours Conclusion Further reading Introduction This model is an approximate version of knn model which is difficult to be implemented with large data set. In contrast to knn model that looks for the exact ...
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Predicting images using Convolutional neural network

April 24, 2020 | Modeling with R

Introduction Data preparation Training the model: Model Evaluation Prediction Conclusion Introduction In this article we will make use of the convolutional neural network, the most widely deep learning method used for image classification, object detection,..etc1. For more detail about how it works please click here. We are going be ...
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Bayesian linear regression

April 24, 2020 | Modeling with R

Introduction Data preparation Classical linear regression model Bayesian regression Bayesian inferences PD and P-value Introduction For statistical inferences we have tow general approaches or frameworks: Frequentist approach in which the data sampled from the population is considered as random and the population parameter values, known as null hypothesis, as fixed (...
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Count data Models

January 5, 2020 | Modeling with R

Introduction: Data preparation Data partition Poisson model Quasi poisson model Negative binomial model Hurdle model hurdle model with poisson distribution. hurdle model with negative binomial distribution. Zero inflated model Zero inflated model with poisson distribution Zero inflated model with negative binomial distribution Conclusion: Furhter reading: Introduction: When we deal with ...
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Xgboost model

January 4, 2020 | Modeling with R

Introduction Data preparation Data visualization Data partition Model training Fine tune the hyperparameters Conclusion: Introduction Decision tree1 is a model that recursively splits the input space into regions and defines local model for each resulted region. However, fitting decision tree model to complex data would not yield to accurate prediction ...
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naive bayes

December 18, 2019 | Modeling with R

Introduction Data preparation Data partition train the model Evaluate the model Fine tune the model: Conclusion Introduction Naive bayes model based on a strong assumption that the features are conditionally independent given the class label. Since this assumption is rarely when it is true, this model termed as naive. However, ...
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logistic regression

December 18, 2019 | Modeling with R

Introduction Data preparation Data partition train the model prediction and confusion matrix altering the link function Introduction In this paper we will fit a logistic regression model to the heart disease data uploaded from kaggle website. For the data preparation we will follow the same steps as we did in ...
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knn model

December 15, 2019 | Modeling with R

Introduction Classification Data partition Train the model Prediction and confusion matrix Fine tuning the model Comparison between knn and svm model Regression Introduction In this paper we will explore the k nearest neighbors model using two data sets, the first is Tiatanic data to which we will fit this model ...
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Methods for dealing with imbalanced data

April 9, 2019 | Modeling with R

Introduction Data partition Subsampling the training data Upsampling : downsampling: ROSE: SMOTE: training logistic regression model. without subsampling Upsampling the train set Down sampling the training set. subsampline the train set by ROSE technique Subsampling the train set by SMOTE technique deep learning model (without class weight). deep learning model with ... [Read more...]


February 4, 2019 | Modeling with R

Create slides in Markdown with Academic Academic | Documentation Features Efficiently write slides in Markdown 3-in-1: Create, Present, and Publish your slides Supports speaker notes Mobile friendly slides Controls Next: Right Arrow or Space Previous: Left Arrow Start: Home Finish: End Overview: Esc Speaker notes: S Fullscreen: F Zoom: Alt + Click ... [Read more...]

Introduction to sparklyr

January 22, 2019 | Modeling with R

Introduction Installing sparklyr Installing spark Connecting to spark Importing data Manipulating data Disconnecting saving data Example of modeling in spark Streaming Introduction The programming language R has very powerful tools and functions to do almost every thing we want to do, such as wrangling , visualizing, modeling…etc. However, R such ...
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