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Q: 2. What are the main steps involved in the classification process?

The main steps involved in the classification process are:1. Data Preprocessing: This involves cleaning and transforming the data to ensure its quality and compatibility with the classification algorithm.2. Feature Selection or Extraction: This step involves selecting the most relevant features from the dataset or extracting new features that can improve the classification accuracy.3. Training the Classifier: The classifier is trained using the labeled training data, where the algorithm learns the patterns and relationships between the features and their corresponding classes.4. Model Evaluation: The trained classifier is evaluated using a separate set of data called the testing data to assess its performance and accuracy.5. Prediction: Once the classifier is trained and evaluated, it can be used to predict the class or category of new, unseen data based on the learned patterns and relationships.

Directions for Questions 1 to 5: Choose the word which is least like other words in the group.
Q1. Choose the correct word.
1. Zebra
2. Lion
3. Tiger
4. Horse
5. Giraffe

Correct Answer is Option (4).
Here, all except Horse, are wild animals, while Horse can be domesticated.

Q2. Choose the correct word.
1. Parrot
2. Bat
3. Crow
4. Sparrow
5. Pigeon

Correct Answer is Option (2).
Here, all except Bat, belong to the class of Aves (birds), while Bat is a mammal. Hence, the answer is 2.

Q3. Choose the correct word.
1. Copper
2. Zinc
3. Brass
4. Aluminium
5. Iron

Correct Answer is Option (3).
Here, all except Brass are metals, while Brass is an alloy, Hence, the answer is 3.

Q4. Choose the correct word.
1. Apple
2. Marigold
3. Rose
4. Lily
5. Lotus

Correct Answer is Option (1).
Here, all except Apple are flowers, while Apple is a fruit. Hence, the answer is 1.

Q5. Choose the correct word.
1. January
2. May
3. July
4. August
5. November

Correct Answer is Option (5).
Here, all except November are months having 31 days, while November has 30 days. Hence the answer is 5.

Directions for Questions 6 to 9: Choose the odd pair of words.
Q6. Choose the odd pair.
1. Blacksmith : Anvil
2. Carpenter : Saw
3. Barber: Scissor
4. Goldsmith : Ornaments
5. Sculptor ; Chisel

Correct Answer is Option (4).
In all other pairs, second is the tool used by the first.

Q7. Choose the odd pair.
1. Painter : Gallery
2. Actor : Stage
3. Mason : Wall
4. farmer : Field
5. Worker : Factory

Correct Answer is Option (3).
In all other pairs, second is the working place of the first.

Q8. Choose the odd pair.
1. Cow : Calf
2. Dog : Bitch
3. Lion : Cub
4. Tortoise : Turtle
5. Insect : Larva

Correct Answer is Option (2).
In all other pairs second is the young one of the first, while in 2 second is the female of the first.

Q9. Choose the odd pair.
1. Volume : Litre
2. Time : Seconds
3. Length : Metre
4. Resistance : Ohm
5. Pressure : Barometer

Correct Answer is Option (5).
In all other pairs second is the unit to measure the first. On the other hand, barometer is an instrument.

Q10. Choose the odd pair.
1. White : Dirty
2. Easy : Difficult
3. Brave : Coward
4. End : Beginning

Correct Answer is Option (1).
In all other pairs, the two words are antonyms of each other.

Directions for Questions 11 to 15: In each of the following questions, five pairs of words are given, out of which the words is four pairs bear a certain common relationship. Choose the pairs in which the words are differently related.
Q11. Choose the pairs in which the words are differently related.
1. Shoe : Leather
2. Iron : Axe
3. Table : Wood
4. Jewellery : Gold
5. Shirt : Fabric

Correct Answer is Option (2).
In all other pairs, first is a product made from the second.

Q12. Choose the pairs in which the words are differently related.
1. Mason : Wall
2. Cobbler : Shoe
3. Farmer : Crop
4. Chef : Cook
5. Choreographer : Ballet

Correct Answer is Option (4).
In all other pairs, second is prepared by the first.

Q13. Choose the pairs in which the words are differently related.
1. Daring : Timed
2. Beautiful : Pretty
3. Clear : Vague
4. Youth : Adult
5. Native : Alien

Correct Answer is Option (2).
In all other pairs, the two words are antonyms of each other.

Q14. Choose the pairs in which the words are differently related.

1. See : Eye
2. Hear : Ears
3. Smell : Nose
4. Touch : Skin
5. Tongue : Taste

Correct Answer is Option (5).
In all other pairs, first denotes the function performed by the second.

Q15. Choose the pairs in which the words are differently related.
1. Bottle : Wine
2. Cup : Tea
3. Pitcher : Water
4. Ball : Bat
5. Inkpot : Ink

Correct Answer is Option (4).
In all other pairs, first is used to hold the second.

Directions for Questions 16 to 20: In each of the following questions, certain pairs of words are given, out of which the words in all pairs except one, bear a certain common relationship. Choose the pair in which the words are differently related.
Q16. Choose the pair in which the words are differently related.
1. Car : Road
2. Ship : Sea
3. Rocket : Space
4. Aeroplane : Pilot

Correct Answer is Option (4).
In all other pairs, first is the means of transport on the medium denoted by the second.

Q17. Choose the pair in which the words are differently related.
1. Beautician : Parlour
2. Chemist : Medicine
3. Lawyer : Court
4. Engineer : Site

Correct Answer is Option (2).
In all other pairs, second is the place where first works.

Q18. Choose the pair in which the words are differently related.
1. Saw : Wood
2. Pen : Paper
3. Author : Book
4. Chalk : Blackboard

Correct Answer is Option (3).
In all other pares, first is the tool which works over the second.

Q19. Choose the pair in which the words are differently related.
1. Water : Thirst
2. Talent: Education
3. Food: Hunger
4. Air : Suffocation

Correct Answer is Option (2).
In all other pairs, lack of first causes the second.

Q20. Choose the pair in which the words are differently related.
1. Apple : Jam
2. Lemon : Citrus
3. Orange : Squash
4. Tomato : Pury

Correct Answer is Option (2).
In all other pairs, second is the form in which the first is preserved.

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FAQs on Questions with Answers: Classification - General Intelligence and Reasoning for SSC CGL

1. What is classification in machine learning?

Classification in machine learning is a supervised learning technique that involves categorizing data into predefined classes or categories. It is used to predict the class or category of new, unseen data based on patterns and features identified in the training data.

2. What are the main steps involved in the classification process?

The main steps involved in the classification process are: 1. Data Preprocessing: This involves cleaning and transforming the data to ensure its quality and compatibility with the classification algorithm. 2. Feature Selection or Extraction: This step involves selecting the most relevant features from the dataset or extracting new features that can improve the classification accuracy. 3. Training the Classifier: The classifier is trained using the labeled training data, where the algorithm learns the patterns and relationships between the features and their corresponding classes. 4. Model Evaluation: The trained classifier is evaluated using a separate set of data called the testing data to assess its performance and accuracy. 5. Prediction: Once the classifier is trained and evaluated, it can be used to predict the class or category of new, unseen data based on the learned patterns and relationships.

3. What are some commonly used classification algorithms in machine learning?

Some commonly used classification algorithms in machine learning are: 1. Logistic Regression: It is a statistical algorithm that predicts the probability of a binary outcome based on the relationship between the dependent variable and one or more independent variables. 2. Decision Trees: Decision trees create a model that predicts the value of a target variable by learning simple decision rules inferred from the features in the training data. 3. Random Forest: Random forest is an ensemble learning method that combines multiple decision trees to create a more accurate and robust classifier. 4. Support Vector Machines (SVM): SVM is a binary classification algorithm that separates data points into different classes by finding the optimal hyperplane that maximally separates the classes. 5. Naive Bayes: Naive Bayes is a probabilistic classifier based on Bayes' theorem that assumes independence between the features and predicts the class based on the highest probability.

4. How is accuracy measured in classification?

Accuracy is a commonly used metric to measure the performance of a classification model. It is calculated by dividing the number of correctly classified instances by the total number of instances in the testing data. A higher accuracy value indicates a more accurate classifier. Mathematically, accuracy can be expressed as: Accuracy = (Number of correctly classified instances / Total number of instances) * 100 However, accuracy alone may not be sufficient to evaluate the performance of a classifier, especially when the dataset is imbalanced or when the misclassification of certain classes is more critical than others. In such cases, other metrics such as precision, recall, and F1 score are also considered.

5. What is the difference between binary and multi-class classification?

Binary classification involves categorizing data into two distinct classes or categories. The classifier predicts whether an instance belongs to one class or the other. Examples of binary classification problems include spam email detection (spam or not spam) or tumor classification (malignant or benign). On the other hand, multi-class classification involves categorizing data into more than two classes or categories. The classifier predicts the class to which an instance belongs out of multiple predefined classes. Examples of multi-class classification problems include image recognition (identifying different objects in an image) or sentiment analysis (categorizing text into positive, negative, or neutral sentiments).

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