Text Regression
Text-based regression predicts a continuous target variable using features extracted from text — TF-IDF scores, embeddings, or n-grams — as the independent variables. Building on the text-as-data programme consolidated by Gentzkow, Kelly and Taddy (2019), it lets a numeric outcome such as a price, a rating, or a sentiment score be estimated directly from documents, and is widely used in social-science, economics, and finance applications.
Rekodi ya chanzo
Nukuu zimehamishwa kwa uhalisi kutoka kwa rekodi ya chanzo cha mbinu. Hakuna uthibitisho wa kiwango cha dai unaodokezwa kutoka kwao.
- Gentzkow, M., Kelly, B. & Taddy, M. (2019). Text as Data. Journal of Economic Literature, 57(3), 535-574. · DOI 10.1257/jel.20181020
- Taddy, M. (2013). Measuring Political Sentiment on Twitter: Factor Optimal Design for Multinomial Inverse Regression. Technometrics, 55(4), 415-425. · DOI 10.1080/00401706.2013.778791
Madai yaliyotunzwa
Madai yamehifadhiwa katika daftari la ushahidi, kila moja ikiwa na tathmini yake.
Mwonekano huu haubuni tathmini ya dai wakati daftari haina yoyote.
Mbinu zinazohusiana
Zilizotengenezwa kutoka kwa grafu ya mbinu na kuonyeshwa kama uhusiano uliopendekezwa na mashine — hakuna dai la ushahidi linalodokezwa.