Kedis ku xidhan hagaha · Fudud Heerka

Kediska Jahwareerka Matrices

Dib u eeg sida jaahwareerka-matrix tirinta ay u muujiyaan khaladaadka kala soocida, taageer cabbirada caadiga ah, oo ay ku kala duwan yihiin heshiisyada fasalka iyo maktabadda.

Wadooyinka haga ee la xidhiidhaJahwareerka Matrices
Su'aal 1 ee 8

Jahwareerka binary matrix-ka, waa maxay Negative Been ah?

Horudhac su'aal kasta8 su'aalo

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

  1. Jahwareerka binary matrix-ka, waa maxay Negative Been ah?
    • Kiis togan tusaaluhu si khaldan ayuu u saadaaliyay inuu yahay taban
    • Xumaan si sax ah loo saadaaliyay sida taban
    • Taag xun ayaa si khaldan loo saadaaliyay inay tahay mid togan
    • Mid togan ayaa si sax ah loo saadaaliyay inuu yahay mid togan
  2. Saxnimada waxaa loo xisaabiyaa sida:
    • TP / (TP + FN)
    • TP / (TP + FP)
    • TN / (TN + FP)
    • (TP + TN) / wadarta
  3. Halbeegkee cabbira saamiga togan ee dhabta ah ee moodeelku si sax ah u garto?
    • Saxnaanta
    • Gaar ahaan
    • Xusuusnow
    • Saxnaanta
  4. Matrixka jaahwareerka ee dhibka leh 5 fasal, maxay yihiin unugyadu u taagan yihiin?
    • Saadaasha khaldan
    • Wanaagga beenta ah kaliya
    • Tirada guud ee shaybaarada
    • Saadaasha saxda ah ee fasal kasta
  5. Waa maxay sababta saxnaanta kaligeed ay u noqon karto marin habaabin la'aanteed jahawareer?
    • Waxay qarisaa dheelitirka u dhexeeya noocyada kala duwan ee khaladaadka sida wanaagga beenta ah iyo xumaanta beenta ah
    • Saxnimadu mar walba waa khalad
    • Looma xisaabin karo dhibaatooyinka binary
    • Waxay u baahan tahay itimaalka halkii ay ka ahaan lahayd sumadaha
  6. Dhibcaha F1 waa celceliska iswaafajinta ee labada mitir?
    • Saxnimada iyo gaar ahaaneed
    • Saxnaanta iyo dib u soo celinta
    • Dareenka iyo gaar ahaaneed
    • Togan run ah iyo xumaan run ah
  7. In a binary confusion matrix, which count is a False Positive?
    • An actual positive that the model predicts as positive
    • An actual positive that the model predicts as negative
    • An actual negative that the model predicts as positive
    • An actual negative that the model predicts as negative
  8. Why should you check a library's confusion-matrix axis labels before calculating precision or recall?
    • The diagonal always contains false positives
    • Axis order changes the number of observations in the dataset
    • Precision and recall use no confusion-matrix cells
    • Libraries may place true classes in rows and predicted classes in columns, or use a different orientation