The previous posts in this series have covered several ways that business leaders can use to understand and explore how Artificial Intelligence can impact their business. We saw that there are several key ways in which AI advances can improve human productivity in organizations. The last two articles dived into Distillation: automating…Continue
Added by Roy Wilds, PhD, PHEMI Systems on September 11, 2017 at 6:00am — No Comments
In the first post in this series on Artificial Intelligence: Monster or Mentor? we saw that there are several key ways in which AI advances can improve human productivity in organizations. In this article, we’ll look at the first: Distillation.
Distillation is applying AI approaches to automate making large data volumes interpretable. Just like miners distill tons of…Continue
Added by Roy Wilds, PhD, PHEMI Systems on June 23, 2017 at 8:30am — No Comments
Artificial Intelligence (AI) is everywhere these days. It’s simultaneously heralded as both the greatest thing since sliced bread — freeing us from driving cars, diagnosing diseases better, and so on — and the worst thing imaginable— displacing millions of jobs, and a step towards the inevitable AI domination of humans.
Lost in this hyperbole are the many simple, yet effective, enabling innovations that AI makes possible. Just like we rely on machines in…Continue
Added by Roy Wilds, PhD, PHEMI Systems on June 8, 2017 at 8:00am — No Comments
Multicollinearity (Collinearity) is not a new term especially when dealing with multiple regression models. This phenomenon of relationship in between one response variable with the set of predictor variables also include models like classification and regression trees as well as neural networks. Collinearity is infamously famous for inflating the variance of at least one estimated regression coefficient, which can cause the model to predict erroneously and in a business setup it can have an…Continue
Added by Sunil Kappal on March 6, 2017 at 10:00am — No Comments
Linear Model better known as linear regression is one of the most common and flexible analysis framework to identify relationship between two or more variables. The widely used linear model is represented by drawing the best fit line through a series of data points represented on a scatter plot.
For any budding business analyst this should be the starting point to understand how model works at the very core of its design.
Selecting the Variables in Deducer…Continue
Added by Sunil Kappal on February 28, 2017 at 7:00am — No Comments
We are dealing with plethora of data and information in the world today and expectation is to predict and forecast how we can gain competitive advantage based on the information that we have, to act in advance. We look forward to define and furnish various methods based on our gut feel, past historical data, simple mathematical averages, and many more to get an incredibly precise prediction. With advanced analytics and data science, we develop “always-on” forecasting…
As we all know CRISP DM stands for Cross Industry Standard Process for Data Mining is a process model that outlines the most common approach to tackle data driven problems. Per the poll conducted by KDNuggets in 2014 this was and “is” one of the most popular and widest used methodology. This method of gleaning insights out of the data is very dear to the industry experts and data miners.
As the title suggest I will align some of the most useful R packages with this most popular and…Continue
As per the largest market research firm MarketsandMarkets the speech analytics industry will grow to USD 1.60 billion by 2020 at a Compound Annual Growth Rate (CAGR) of 22% from 2015 to 2020. Today the omnichannel world consists of voice, email, chat, social channels, and surveys, and each channel has its own importance.
Therefore, it becomes inevitable for any customer centric organization to ignore the information that can be glean…Continue
As the world is getting more tech savvy and advancements made in the information technology especially in the healthcare industry has opened areas in data mining and machine learning. Within the area of data mining one technique which has gained a lot of popularity as well as skepticism among the auditors and fraud detectives is Benford’s Law or “The Law of First digit.
In the past some researchers in Canada used the Benford’s Law distribution to detect anomalies within the claims…Continue
Best Subset Regression method can be used to create a best-fitting regression model. This technique of model building helps to identify which predictor (independent) variables should be included in a multiple regression model(MLR).
This method comprises of scrutinizing all of the models created from all possible permutation combination of predictor variables. This technique uses the R Squared value to check for the best model. Considering the level of complexity involved in creating…Continue
An insightful person once said, “Prediction is like driving your car forward by looking only at the rearview mirror!”. If the road is dead-straight, you are good . . . UNLESS there is a stalled vehicle ahead in the middle of the road.
We should consider short-term and long-term prediction separately. Long-term prediction is nearly a lost cause. In the 80’s and 90’s, chaos and complexity theorists showed us that things can spin out of control even when we have perfect…Continue
Added by PG Madhavan on January 26, 2016 at 2:08pm — No Comments
There are various offerings out there if you want to use machine learning in your analysis nowadays. Nick WIlson spent his internship at BigML comparing three SaaS Machine Learning Services (BigML, Prior Knowledge and Google Prediction API), with WEKA as a benchmark. He wrote a series of blog posts about his findings. In his final post he gives a summary of his work, with links to the different blog posts for details. He let me re-blog his summary here.
Added by Jos Verwoerd on September 13, 2012 at 3:37am — No Comments