Kedis ku xidhan hagaha · Fudud Heerka
Kedis kala soocida qoraalka
Tijaabi shaqada summada qoraalka, hawlaha summada badan leh, dheellitirnaan la'aanta, dib-u-celinta, isticmaalka eber-ku-dhufashada ee hawsha gaarka ah, ku-xidhka, xisaabinta saxda ah, iyo buundooyinka soo-saarka.
Su'aal 1 ee 8
How does a text classifier structure the output for an input document?
Horudhac su'aal kasta8 su'aalo
Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.
- How does a text classifier structure the output for an input document?
- By necessarily translating it into another language
- By assigning one or more predefined category labels
- By generating only a new unrelated paragraph
- By changing its compressed file format
- Xaaladdee ayaa tusaale u ah soocidda summada-badan?
- Ku calaamadaynta iimaylka sidii spam ama aan spam ahayn
- Ku-wareejinta tigidhka si sax ah waax
- Doorashada hal xiddig oo qiimeeya
- Ku dhejinta maqaal labadaba 'siyaasad' iyo 'dhaqaale' labadaba hal mar
- On a text dataset dominated by one class, what can a high overall accuracy conceal?
- An inability to calculate any metric
- Proof that recall equals one for every category
- Failure to identify cases of a rare class
- A guarantee that every minority example is correct
- Maxay dib u xasuusashadu ku cabbirtaa hawsha kala-soocidda?
- Immisa ka mid ah kiisaska dhabta ah ee nidaamku si guul leh u qabsaday
- Immisa shay oo calaamadeysan ayaa dhab ahaantii sax ahaa
- Sida dhakhsaha ah ee moodelku u socdo
- Intee in le'eg ayaa moodelku yahay
- In task-specific zero-shot text classification, what is absent for the new classification task?
- All model pretraining of any kind
- Every description of the candidate categories
- The ability to use any learned representation
- Labeled training examples for that task
- How can learned text embeddings contribute to a classification pipeline?
- They guarantee perfect predictions on every new domain
- They provide numerical features used to compute label scores
- They delete every grammatical distinction by definition
- They replace all label definitions with filenames
- A stated text-classification evaluation has six true positives and two false positives. What is precision for the designated positive class?
- 75 percent
- 25 percent
- 100 percent
- Six percent
- Which output-score design permits several text labels to score highly at once rather than requiring scores to sum to one?
- A single softmax over mutually exclusive classes
- A rule requiring exactly one positive label
- A separate sigmoid output for each label
- A filename-only representation without label scores