Decision Tree Modeling Using R Certification Training

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Decision Tree Modeling Using R Certification Training

Become a Decision Tree Modeling expert using R platform by mastering concepts like Data design, Regression Tree, Pruning and various algorithms like CHAID, CART, ID3, GINI and Random forest.

$139.00 $97.00

Online self paced classes

Online Self Learning Courses are designed for self-directed training, allowing participants to begin at their convenience with structured training and review exercises to reinforce learning. You’ll learn through videos, PPTs and complete assignments, projects and other activities designed to enhance learning outcomes, all at times that are most convenient to you.

Introduction to Decision Tree

Answer: Learning Objectives - In this module, you will understand What is a Decision Tree and what are the benefits. What are the core objectives of Decision Tree modelling, How to understand the gains from the Decision Tree and How does one apply the same in business scenarios Topics - Decision Tree modeling Objective, Anatomy of a Decision Tree, Gains from a decision tree (KS calculations), and Definitions related to objective segmentations

Data design for Modelling

Answer: Learning Objectives - In this module, you will learn how to design the data for modelling Topics - Historical window, Performance window, Decide performance window horizon using Vintage analysis, General precautions related to data design

Data treatment before Modelling

Answer: Learning Objectives - In this module, you will learn how to ensure Data Sanity check and you will also learn to perform the necessary checks before modelling Topics - Data sanity check-Contents, View, Frequency Distribution, Means / Uni-variate, Categorical variable treatment, Missing value treatment guideline, capping guideline

Classification of Tree development and Algorithm details

Answer: Learning Objectives - In this module, you will learn to use R and the Algorithm to develop the Decision Tree. Topics - Preamble to data, Installing R package and R studio, Developing first Decision Tree in R studio, Find strength of the model, Algorithm behind Decision Tree, How is a Decision Tree developed?, First on Categorical dependent variable, GINI Method, Steps taken by software programs to learn the classification (develop the tree), Assignment on decision tree

Industry practice of Classification tree-Development, Validation and Usage

Answer: Learning Objectives - In this module you will understand how Classification trees are Developed, Validated and Used in the industry Topics - Discussion on assignment, Find Strength of the model, Steps taken by software program to implement the learning on unseen data, learning more from practical point of view, Model Validation and Deployment.

Regression Tree and Auto Pruning

Answer: Learning Objectives - In this module you will understand the Advance stopping criteria of a decision tree. You will also learn to develop Decision Trees for numerous outcomes. Topics - Introduction to Pruning, Steps of Pruning, Logic of pruning, Understand K fold validation for model, Implement Auto Pruning using R, Develop Regression Tree, Interpret the output, How it is different from Linear Regression, Advantages and Disadvantages over Linear Regression, Another Regression Tree using R

CHAID Algorithm

Answer: Learning Objectives - In this module you will learn what is Chi square and CHAID and their working and also the difference between CHAID and CART etc.. Topics - Key features of CART, Chi square statistics, Implement Chi square for decision tree development, Syntax for CHAID using R, and CHAID vs CART.

Other Algorithms

Answer: Learning Objectives - In this module you will learn about ID3, Entropy, Random Forest and Random Forest using R Topics - Entropy in the context of decision tree, ID3, Random Forest Method and Using R for Random forest method, Project work

How will I execute the practicals?

Answer: For your practical work, we will help you setup Edureka's Virtual Machine in your System. This will be a local access for you. The required installation guide is present in LMS.

What if I miss a class?

Answer: \"You will never miss a lecture at CertAddda You can choose either of the two options: View the recorded session of the class available in your LMS. You can attend the missed session, in any other live batch.\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\"

How soon after Signing up would I get access to the Learning Content?

Answer: Post-enrolment, the LMS access will be instantly provided to you and will be available for lifetime. You will be able to access the complete set of previous class recordings, PPTs, PDFs, assignments. Moreover the access to our 24x7 support team will be granted instantly as well. You can start learning right away.

What if I have queries after I complete this course?

Answer: Your access to the Support Team is for lifetime and will be available 24/7. The team will help you in resolving queries, during and after the course.

Do I get any assistance from CertAdda to fill up the application form?

Answer: Yes, we will guide you on how to apply & fill up the ACP® application form in PMI® website. You can use the following link to apply for examination: Apply for Exam

Will I get placement assistance?

Answer: To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\"create your resume\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\" option.

Is the course material accessible to the students even after the course training is over?

Answer: Yes, the access to the course material will be available for lifetime once you have enrolled into the course.

Who are the instructors?

Answer: All the instructors at CertAdda are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by CertAdda for providing an awesome learning experience to the participants.

What if I have more queries?

Answer: You can give us a CALL at +91 8178510474 / +91 9967920486 OR email at admin@certadda.com