predictive modelling


  • [2] In many cases, the model is chosen on the basis of detection theory to try to guess the probability of an outcome given a set amount of input data, for example given an
    email determining how likely that it is spam.

  • [citation needed] Some models include a wide range of predictive input beyond basic telemetry including advanced driving behaviour, independent crash records, road history,
    and user profiles to provide improved risk models.

  • [citation needed] Possible fundamental limitations of predictive models based on data fitting History cannot always accurately predict the future.

  • Customer relationship management[edit] Predictive modelling is used extensively in analytical customer relationship management and data mining to produce customer-level models
    that describe the likelihood that a customer will take a particular action.

  • So far, no statistical models that attempt to predict equity market prices based on historical data are considered to consistently make correct predictions over the long term.

  • [10] Lead tracking systems[edit] See also: behavioral analytics Predictive modelling gives lead generators a head start by forecasting data-driven outcomes for each potential

  • Models can use one or more classifiers in trying to determine the probability of a set of data belonging to another set.

  • [9] proposed a deep learning model for estimating short-term life expectancy (3 months) of the patients by analyzing free-text clinical notes in the electronic medical record,
    while maintaining the temporal visit sequence.

  • Using relations derived from historical data to predict the future implicitly assumes there are certain lasting conditions or constants in a complex system.

  • [1] Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred.

  • The high accuracy and explain-ability of the PPES-Met model may enable the model to be used as a decision support tool to personalize metastatic cancer treatment and provide
    valuable assistance to physicians.

  • Development of quantitative methods and a greater availability of applicable data led to growth of the discipline in the 1960s and by the late 1980s, substantial progress
    had been made by major land managers worldwide.

  • To provide explain-ability, they developed an interactive graphical tool that may improve physician understanding of the basis for the model’s predictions.

  • This is extensively employed in usage-based insurance solutions where predictive models utilise telemetry-based data to build a model of predictive risk for claim likelihood.

  • By using predictive modelling in their cultural resource management plans, they are capable of making more informed decisions when planning for activities that have the potential
    to require ground disturbance and subsequently affect archaeological sites.

  • [11] Notable failures of predictive modeling[edit] Although not widely discussed by the mainstream predictive modeling community, predictive modeling is a methodology that
    has been widely used in the financial industry in the past and some of the major failures contributed to the financial crisis of 2007–2008.

  • However, no matter how extensive the collector considers his/her selection of the variables, there is always the possibility of new variables that have not been considered
    or even defined, yet are critical to the outcome.

  • One particularly memorable failure is that of Long Term Capital Management, a fund that hired highly qualified analysts, including a Nobel Memorial Prize in Economic Sciences
    winner, to develop a sophisticated statistical model that predicted the price spreads between different securities.

  • In the former, one may be entirely satisfied to make use of indicators of, or proxies for, the outcome of interest.

  • Parametric models make “specific assumptions with regard to one or more of the population parameters that characterize the underlying distribution(s)”.

  • A model of the change in probability allows the retention campaign to be targeted at those customers on whom the change in probability will be beneficial.

  • [citation needed] Predictive modeling is still extensively used by trading firms to devise strategies and trade.


Works Cited

[‘Geisser, Seymour (1993). Predictive Inference: An Introduction. Chapman & Hall. p. [page needed]. ISBN 978-0-412-03471-8.
2. ^ Finlay, Steven (2014). Predictive Analytics, Data Mining and Big Data. Myths, Misconceptions and Methods (1st ed.). Palgrave
Macmillan. p. 237. ISBN 978-1137379276.
3. ^ Sheskin, David J. (April 27, 2011). Handbook of Parametric and Nonparametric Statistical Procedures. CRC Press. p. 109. ISBN 978-1439858011.
4. ^ Cox, D. R. (2006). Principles of Statistical Inference.
Cambridge University Press. p. 2.
5. ^ Willey, Gordon R. (1953), “Prehistoric Settlement Patterns in the Virú Valley, Peru”, Bulletin 155. Bureau of American Ethnology
6. ^ Heidelberg, Kurt, et al. “An Evaluation of the Archaeological Sample Survey
Program at the Nevada Test and Training Range”, SRI Technical Report 02-16, 2002
7. ^ Jeffrey H. Altschul, Lynne Sebastian, and Kurt Heidelberg, “Predictive Modeling in the Military: Similar Goals, Divergent Paths”, Preservation Research Series
1, SRI Foundation, 2004
8. ^ “Hospital Uses Data Analytics and Predictive Modeling To Identify and Allocate Scarce Resources to High-Risk Patients, Leading to Fewer Readmissions”. Agency for Healthcare Research and Quality. 2014-01-29. Retrieved
9. ^ Banerjee, Imon; et al. (2018-07-03). “Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) Utilizing Free-Text Clinical Narratives”. Scientific Reports. 8 (10037 (2018)): 10037. Bibcode:2018NatSR…810037B.
doi:10.1038/s41598-018-27946-5. PMC 6030075. PMID 29968730.
10. ^ “Predictive-Model Based Trading Systems, Part 1 – System Trader Success”. System Trader Success. 2013-07-22. Retrieved 2016-11-25.
11. ^ “Predictive Modeling for Call Tracking”.
Phonexa. 2019-08-22. Retrieved 2021-02-25.
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