The caret package (short for Classification And REgression Training) is a set of functions that attempt to streamline the process for creating predictive models. The package contains tools for: data splitting; pre-processing; feature selection. A caret is a blinking line, block, or bitmap in the client area of a window. The caret typically indicates the place at which text or graphics will be inserted. The following illustration shows some common variations in the appearance of the caret. Applications can create a caret, change its blink time, and display, hide, or relocate the caret. Definition of caret.: a wedge-shaped mark made on written or printed matter to indicate the place where something is to be inserted.
The caret package (short for Classification And REgression Training) is a set of functions that attempt to streamline the process for creating predictive models. The package contains tools for:
- data splitting
- pre-processing
- feature selection
- model tuning using resampling
- variable importance estimation
as well as other functionality.
There are many different modeling functions in R. Some have different syntax for model training and/or prediction. The package started off as a way to provide a uniform interface the functions themselves, as well as a way to standardize common tasks (such parameter tuning and variable importance).
The current release version can be found on CRAN and the project is hosted on github.
Some resources:
- The book Applied Predictive Modeling features caret and over 40 other R packages. It is on sale at Amazon or the the publisher’s website. There is a companion website too.
- There is also a paper on caret in the Journal of Statistical Software. The example data can be obtained here(the predictors) and here (the outcomes).
- There is a webinar for the package on Youtube that was organized and recorded by Ray DiGiacomo Jr for the Orange County R User Group.
- At useR! 2014, I was interviewed and discussed the package and the book.
- DataCamp has a beginner’s tutorial on machine learning in R using
caret.
You can always email me with questions,comments or suggestions.
These HTML pages were created using bookdown.
Core Leadership
John Keller, California State University System; Bruce Johnson, University of Arizona; Jordan Gerton, the University of Utah; and Elisa Stone, University of California, Berkeley
Announcements
January 2020
CARET has a newly published review article on research experiences. This paper provides a comprehensive review of 307 papers published between 2007 and 2017 that include course-based undergraduate research experiences (CUREs), undergraduate research experiences (UREs), and teacher research experiences (TREs) programs, with a special focus on research experiences for K–12 teachers. The field of biology was the predominant scientific disciplinary focus. Findings suggest a lack of studies explicitly targeting 1) participation and outcomes related to learners from underrepresented populations, 2) a theoretical framework that guides program design and analysis, and, for TREs, 3) methods for translation of research experiences into K–12 instructional practices, and 4) measurement of impact on K–12 instructional practices.
Krim, J. S., Coté, L. E., Schwartz, R. S., Stone, E. M., Cleeves, J. J., Barry, K. J., .. & Keller, J. M. (2019). Models and Impacts of Science Research Experiences: A Review of the Literature of CUREs, UREs, and TREs. CBE—Life Sciences Education, 18(4), ar65. Available at https://www.lifescied.org/doi/full/10.1187/cbe.19-03-0069 .
Caretrust Reit
About CARET
The Collaborative Around Research Experiences for Teachers (CARET) promotes cross-institutional collaboration involving research and assessment into commonalities, differences, and impacts of teacher-researcher programs, and contributes to the body of knowledge around research experiences for undergraduates. CARET is a collaborative of 21 individuals representing 14 institutions with interest an investment in teacher researcher programs. In total, these institutions support eight teacher research experience programs for preservice and in-service teachers. Through the efforts of this RAC, we have created several products to propel the work: a Theory of Change diagram, an accompanying Theory of Change description, a logic model, the coding guide that governed our literature review, the common assessment framework that built our shared assessment instrument, and a manuscript under review.
Shared Assessment Instrument
During academic year 2016-17, the collaborative developed a pilot assessment instrument that could be administered across teacher researcher programs. This shared assessment instrument was administered to 130 participants in four programs at the beginning of Summer 2017 to 190 participants in six programs at the end of Summer 2017. The results from this pilot administration were analyzed at a CARET Meeting held in San Diego California in January 2018. Minor modifications were made to the instrument which has been re-administered to 120 participants in four programs at the beginning of Summer 2018 and to 115 participants in four programs at the end of Summer 2018. During Summer 2019, the tool was administered to 55 participants in two programs at the beginning of the Summer and the post survey is currently being administered.
Literature Review Published
During the 2018-19 academic year, CARET completed a literature review of 307 peer-reviewed publications regarding undergraduate research experiences (UREs), course based undergraduate research experiences (CUREs), and teacher research experiences (TREs). In December 2019, the Collaborative Around Research Experiences for Teachers (CARET) published a literature review titled 'Models and Impacts of Science Research Experiences: A Review of the Literature of CUREs, UREs, and TREs' in CBE – Life Sciences Education16F16F[1]. This paper reviews recent research regarding undergraduate research experiences (UREs), course-based undergraduate research experiences (CUREs), and teacher research experiences (TREs). Central findings include 'lack of studies explicitly targeting 1) participation and outcomes related to learners from underrepresented populations, 2) a theoretical framework that guides program design and analysis, and, for TREs, 3) methods for translation of research experiences into K–12 instructional practices, and 4) measurement of impact on K–12 instructional practices.' This article was also featured in an ARISE blogpost titled 'Is This 'TRE' for Me? A Review of the Literature on Teacher Research Experiences and Impact on K-12 STEM Classrooms' published on April 6, 2020.
Article: Krim, J. S., Coté, L. E., Schwartz, R. S., Stone, E. M., Cleeves, J. J., Barry, K. J., .. & Keller, J. M. (2019). Models and impacts of science research experiences: A review of the literature of CUREs, UREs, and TREs. CBE—Life Sciences Education, 18(4), ar65. Prodec paint brushes review.
Activities after funding from NSEC
In 2019, CARET submitted a DKR-12 Conference Proposal to bring together stakeholders and instrument development experts to develop concept papers and collaborative research investigations around TREs. The proposal received favorable reviews but was not funded. Since March 2020, CARET has been meeting biweekly and weekly to build upon the findings of the above works to advance the collaborative's research agenda, with plans to submit a DRK-12 proposal to NSF.
CARET RAC Members
- University of Colorado Boulder - John Keller
- University of California, Berkeley - Berkeley Science and Math Initiative (BSMI) - Elisa Stone, Edward Ham, & Laleh Cote
- Southern Illinois University - Center for STEM - Sharon Locke, Jessica Krim, & Kelly Barry
- Georgia State University - Center for STEM Education Initiatives - Renee Schwartz
- University of Utah - Center for Science and Mathematics Education - Jordan Gerton & Jessica Cleeves
- University of Arizona - UA STEM Learning Center - Bruce Johnson, Sanlyn Buxner, & Lisa Elfring
- University of Oregon - STEM Careers through Outreach, Research, & Education (STEM CORE) -Bryan Rebar
- Wichita State University - STEM Initiative, College of Education & Fairmount Center for Science and Mathematics Education -Mara Alagic and Soon Chun Lee
- Cal Poly San Luis Obispo - Center for Engineering, Science, and Math Education - Stamatis Vokos
- San Francisco State University - Center for Science and Math Education (CSME) - Larry Horvath, Eric Hsu, & Jamie Chan
- Purdue University - Discovery Learning Research Center - Willie Burgess
- Murdock Charitable Trust – Kim Newman, Jill Tatum
- Ignited – Shari Liss
- Pennsylvania State University – Center for Science and the Schools - Kathleen Hill, Amanda Smith
Additional RAC participants
- Kansas State University - Center for Science Education - Kimberly Staples
- Towson University - Center for STEM Excellence - Mary Stapleton
- Caltech - Center for Teaching, Learning & Outreach - Julius Su & James Maloney
- North Carolina State University - STEM Ed - Kathy Cabe Trundle
Caret Browsing
Related References/Resources
Caret Text Editor
- Auchincloss, L.C., Laursen, S.L., Branchaw, J.L., Eagan, K., Graham, M., Hanauer, D.I., Lawrie, G., McLinn, C.M., Pelaez, N., Rowland, S., Towns, M., Trautmann, N.M., Varma-Nelson, P., Weston, T.J., and Dolan, E.L. (2014) Assessment of Course-Based Undergraduate Research Experiences: A Meeting Report. CBE Life Sci Educ. 2014 Spring; 13(1): 29–40. doi: 10.1187/cbe.14-01-0004.
Committee on Science, Engineering, and Public Policy. (2011). Expanding Underrepresented Minority Participation. Washington, DC: The National Academies Press. - Eagan, Jr., M.K., Hurtado, S., Chang, M.J., Garcia, G.A., Herrera, F.A., and Garibay, J.C. (2013). Making a difference in science education: The impact of undergraduate research programs American Educational Research Journal, 50, 683-713.
Linn, M.C., Palmer, E., Baranger, A., Gerard, E., and E. Stone. (2015). Undergraduate research experiences: Impacts and opportunities. Science 347, 627 - Sadler, T.D., Burgin, S., McKinney, L., Ponjuan, L. (2010) Learning science through research apprenticeships: A critical review of the literature. J. Res. Sci. Teach. 47, 235 (2010). doi:
10.1002/tea.20326.