- AExcel data
- BData from mySQL DB
- CImage
Unstructured Data Classification - Quiz
- ARandom Forest
- BSGDClassifier
- CSVM
- DStratifiedShuffleSplit
- Adocument
- BTF value
- Cword
- DTF-IDF value
- AInitialize -> Train -> Predict -> Evaluate
- BInitialize -> Evaluate -> Train -> Predict
- CTrain -> Test -> Initialize -> Predict
- DNone of the options
- ATrue
- BFalse
- AData Analysis -> Pre-Processing -> Model Building -> Predict
- BPre-Processing -> Model Building -> Predict
- CPre-Processing -> Predict -> Train
- DData Analysis -> Pre-Processing -> Predict -> Train
- AUnstructured data
- BStructured data
- Adocument
- BTF-IDF value
- CTF value
- Dword
- Abottle
- Bjango
- Csklearn
- Dpillow
- Afrom nltk import sentence_tokenize, Word_tokens =sentence_tokenize(sentence)
- Bfrom nltk.tokenizer import word_tokenizer, Word_tokens =word_tokenizer(sentence)
- Cfrom nltk import tokenize_words, Word_tokens =tokenize_words(sentence)
- Dfrom nltk.tokenize import word_tokenize, Word_tokens =word_tokenize(sentence)
Results:
🟢 Correct Answers: 🔴 Wrong Answers:
🟢 Correct Answers: 🔴 Wrong Answers:
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Quiz Information
Quiz Information
Quiz Platform FAQ
General Information
- Number of Questions: Each quiz consists of 10 questions.
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Quiz Analytics
Unstructured Data Classification - Quiz
Guest User
Time Taken: Questions: Answered: Not Answered:
Correct Answer:
Wrong Answer:
Percentage: %
- A. Excel data
- B. Data from mySQL DB
- C. Image
Remarks:
Explanation: Image
- A. Random Forest
- B. SGDClassifier
- C. SVM
- D. StratifiedShuffleSplit
Remarks:
Explanation: StratifiedShuffleSplit
- A. document
- B. TF value
- C. word
- D. TF-IDF value
Remarks:
Explanation: document
- A. Initialize -> Train -> Predict -> Evaluate
- B. Initialize -> Evaluate -> Train -> Predict
- C. Train -> Test -> Initialize -> Predict
- D. None of the options
Remarks:
Explanation: Initialize -> Train -> Predict -> Evaluate
- A. True
- B. False
Remarks:
Explanation: False
- A. Data Analysis -> Pre-Processing -> Model Building -> Predict
- B. Pre-Processing -> Model Building -> Predict
- C. Pre-Processing -> Predict -> Train
- D. Data Analysis -> Pre-Processing -> Predict -> Train
Remarks:
Explanation: Data Analysis -> Pre-Processing -> Model Building -> Predict
- A. Unstructured data
- B. Structured data
Remarks:
Explanation: Unstructured data
- A. document
- B. TF-IDF value
- C. TF value
- D. word
Remarks:
Explanation: word
- A. bottle
- B. jango
- C. sklearn
- D. pillow
Remarks:
Explanation: sklearn
- A. from nltk import sentence_tokenize, Word_tokens =sentence_tokenize(sentence)
- B. from nltk.tokenizer import word_tokenizer, Word_tokens =word_tokenizer(sentence)
- C. from nltk import tokenize_words, Word_tokens =tokenize_words(sentence)
- D. from nltk.tokenize import word_tokenize, Word_tokens =word_tokenize(sentence)
Remarks:
Explanation: from nltk.tokenize import word_tokenize, Word_tokens =word_tokenize(sentence)