Researchers at Columbia University, Princeton and Harvard University have developed a new approach for analyzing big data that can drastically improve the ability to make accurate predictions about medicine, complex diseases, social science phenomena, and other issues.
In a study published in the December 13 issue of Proceedings of the National Academy of Sciences (PNAS), the authors introduce the Influence score, or “I-score,” as a statistic correlated with how much variables inherently can predict, or “predictivity”, which can consequently be used to identify highly predictive variables.
“In our last paper, we showed that significant variables may not necessarily be predictive, and that good predictors may not appear statistically significant,” said principal investigator Shaw-Hwa Lo, a professor of statistics at Columbia University. “This left us with an important question: how can we find highly predictive variables then, if not through a guideline of statistical significance? In this article, we provide a theoretical framework from which to design good measures of prediction in general. Importantly, we introduce a variable set’s predictivity as a new parameter of interest to estimate, and provide the I-score as a candidate statistic to estimate variable set predictivity.”
Current approaches to prediction generally include using a significance-based criterion for evaluating variables to use in models and evaluating variables and models simultaneously for prediction using cross-validation or independent test data.
“Using the I-score prediction framework allows us to define a novel measure of predictivity based on observed data, which in turn enables assessing variable sets for, preferably high, predictivity,” Lo said, adding that, while intuitively obvious, not enough attention has been paid to the consideration of predictivity as a parameter of interest to estimate. Motivated by the needs of current genome-wide association studies (GWAS), the study authors provide such a discussion.
In the paper, the authors describe the predictivity for a variable set and show that a simple sample estimation of predictivity directly does not provide usable information for the prediction-oriented researcher. They go on to demonstrate that the I-score can be used to compute a measure that asymptotically approaches predictivity. The I-score can effectively differentiate between noisy and predictive variables, Lo explained, making it helpful in variable selection. A further benefit is that while usual approaches require heavy use of cross-validation data or testing data to evaluate the predictors, the I-score approach does not rely as much on this as much.
“We offer simulations and an application of the I-score on real data to demonstrate the statistic’s predictive performance on sample data,” he said. “These show that the I-score can capture highly predictive variable sets, estimates a lower bound for the theoretical correct prediction rate, and correlates well with the out of sample correct rate. We suggest that using the I-score method can aid in finding variable sets with promising prediction rates, however, further research in the avenue of sample-based measures of predictivity is needed.”
The authors conclude that there are many applications for which using the I-score would be useful, for example in formulating predictions about diseases with high dimensional data, such as gene datasets, in the social sciences for text prediction or financial markets predictions; in terrorism, civil war, elections and financial markets.
“We’re hoping to impress upon the scientific community the notion that for those of us who might be interested in predicting an outcome of interest, possibly with rather complex or high dimensional data, we might gain by reconsidering the question as one of how to search for highly predictive variables (or variable sets) and using statistics that measure predictivity to help us identify those variables to then predict well,” Lo said. “For statisticians in particular, we’re hoping this opens up a new field of work that would focus on designing new statistics that measure predictivity.”
Receive an email update when we add a new PREDICTION TOOL article.
The Latest on: Accurate predictions
via Google News
The Latest on: Accurate predictions
- AstroTalk stands tall with most accurate and foolproof future predictionson October 18, 2019 at 5:02 pm
And that's exactly what happens if an authentic astrologer predicts your future most accurately without any fallacy. Sounds unbelievable! AstroTalk is an online astrology app for future prediction, ...
- Growth of Metabolomics Market to Be Impacted by Rising Demand for Early and Accurate Diagnostics | Technavioon October 18, 2019 at 10:55 am
These factors are positively influencing the growth of the global metabolomics market. Increasing applications of metabolomics – An emerging trend in the metabolomics market Advances in the prediction ...
- Five burning questions for Clemson against Louisville — and a predictionon October 18, 2019 at 2:15 am
Both of them are very accurate passers,” Swinney said ... Potter will be called upon if Clemson needs a long field goal. Prediction: Louisville should be able to score some points against a Clemson ...
- Combination of AI tool and radiologists identifies breast cancer with 90% accuracyon October 17, 2019 at 1:58 pm
Accuracy was measured in the frequency of correct predictions. In addition, the researchers designed the study AI model to first consider very small patches of the full resolution image separately to ...
- Clinical-learning versus machine-learning for transdiagnostic prediction of psychosis onset in individuals at-riskon October 17, 2019 at 10:42 am
To date, there is no empirical research comparing the prognostic accuracy of these two methods for the prediction of psychosis onset. In a first experiment, no improved performance was observed when ...
- CFB Predictions and Preview: Michigan Wolverines at Penn State Nittany Lionson October 17, 2019 at 4:57 am
The Wolverines are still in the hunt at No. 16, while the Nittany Lions are knocking on the door at No. 7. However, "good game" hasn't been an accurate description recently in a rivalry that has been ...
- Editorial: With accurate information, turnpike can plan upgradeson October 16, 2019 at 9:00 pm
The study’s off-base predictions would be slightly amusing if it weren’t for the possibility ... Barr said he didn’t think the inaccurate traffic numbers caused problems for the 2018 bond issue, as it ...
- Historically Accurate Election Forecaster Predicts Trump Will Win by Even Greater Margin in 2020on October 15, 2019 at 3:38 pm
Though President Donald Trump currently trails several leading Democratic candidates in early national polls, a research firm with a historically accurate model has him winning the 2020 election ...
- Trump in a landslide? This historically accurate model predicts exactly thaton October 15, 2019 at 2:46 pm
President Donald Trump has a love/hate relationship with polls, surveys and predictions. He loves the ones that paint him in a positive light, and, of course, he hates all those “fake” ones that don’t ...
via Bing News