Does it sound familiar to you? In order to get an idea of how to choose a parameter for a given classifier, you have to cross reference to a number of papers or books, which often turn out to present competing arguments for or against a certain parameterization choice but with few applications to real-world problems.
For example, you may find a few papers discussing optimal selection of K in…Continue
This article was written by Thomas Legoff.
Artificial intelligence – or AI – is a true part of our world, as well as a substantial hub of interest for science and business. Companies are ferociously investing in, engaging in and including artificial intelligence in their operations. It is a fascinating technology that enables new options for companies, from detecting security intrusions…Continue
Added by Emmanuelle Rieuf on June 5, 2017 at 8:30am — No Comments
It speaks volumes of the world we live in today when headlines such as “The world’s most valuable resource is no longer oil, but data” and “Why Data May Be More Valuable Than Dollars” are commonplace. With the explosion of IoT and with that 2.5 quintillion bytes of data being created per day, the underlying power of this data comes as no surprise.
Unlike gold however, data is ubiquitous and being created at an exponential rate. So where’s the value in something that is everywhere?…Continue
Added by Amy Flippant on June 5, 2017 at 12:30am — No Comments
Added by Sandeep Raut on June 4, 2017 at 7:30pm — No Comments
Monday newsletter published by Data Science Central. Previous editions can be found here. The contribution flagged with a + is our selection for the picture of the week.
Added by Vincent Granville on June 3, 2017 at 9:00am — No Comments
Introduction to R Programming Language
R is an intense dialect utilized broadly for information investigation and measurable registering. It was created in the mid 90s. It is a standout amongst the most well known dialects utilized by analysts, information experts, scientists, and advertisers to recover, clean, dissect,…Continue
Added by Johny Basha on June 2, 2017 at 8:30pm — No Comments
Cross Validation is often used as a tool for model selection across classifiers. As discussed in detail in the following paper https://ssrn.com/abstract=2967184, Cross Validation is typically performed in the following steps:
Added by Zhongmin Luo on June 2, 2017 at 7:00pm — No Comments
Enterprise business models evolve over time for many reasons. The Internet has been a key factor driving enterprise business model change in recent years. The recent popularity of smartphones has disrupted consumer habits in travel, investment, entertainment, communication, social engagement, dining, shopping and many daily activities. Consequently, enterprises have been forced to change their business models. While some changes are progressive, others are…Continue
Added by Sing Koo on June 1, 2017 at 4:30pm — No Comments
This article explains how to select important variables using boruta package in R. Variable Selection is an important step in a predictive modeling project. It is also called 'Feature Selection'. Every private and public agency has started tracking data and collecting information of various attributes. It results to access to too many predictors for a predictive model. But not every variable is important for prediction of a particular task. Hence it is essential to…Continue
Here is our selection of featured articles and resources published since Monday.Continue
Added by Vincent Granville on June 1, 2017 at 8:59am — No Comments
Over the course of the last two decades, the internet has become nearly ubiquitous. From the ages of rare dial-up connections, our relatively reliable 4G network and endless options for free Wi-Fi at public establishments is its own kind of digital paradise. However, the internet isn’t perfect, and if we want to build a world where our entire population has fast,…Continue
Added by Larry Alton on June 1, 2017 at 7:00am — No Comments
Random Forests algorithm has always fascinated me. I like how this algorithm can be easily explained to anyone without much hassle. One quick example, I use very frequently to explain the working of random forests is the way a company has multiple rounds of interview to hire a candidate. Let me elaborate.
Say, you appeared for the position of Statistical analyst at WalmartLabs. Now like most of the companies, you don't just have one round of interview. You…