Topic 1 Question 63
A retail company intends to use machine learning to categorize new products. A labeled dataset of current products was provided to the Data Science team. The dataset includes 1,200 products. The labeled dataset has 15 features for each product such as title dimensions, weight, and price. Each product is labeled as belonging to one of six categories such as books, games, electronics, and movies. Which model should be used for categorizing new products using the provided dataset for training?
AnXGBoost model where the objective parameter is set to multi:softmax
A deep convolutional neural network (CNN) with a softmax activation function for the last layer
A regression forest where the number of trees is set equal to the number of product categories
A DeepAR forecasting model based on a recurrent neural network (RNN)
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コメント(16)
Ans: A XGBoost multi class classification. https://medium.com/@gabrielziegler3/multiclass-multilabel-classification-with-xgboost-66195e4d9f2d
CNN is used for image classificaiton problems
👍 33rsimham2021/09/23Answer is A. This a classification problem thus XGBoost and the fact that there are six categories SOFTMAX is the right activation function
👍 14JayK2021/09/30100% is A; the the others are clearly wrong
Convolutional Neural Network (ConvNet or CNN) is a special type of Neural Network used effectively for image recognition and classification Recurrent neural networks (RNN) are a class of neural networks that is powerful for modeling sequence data such as time series or natural language
👍 5syu31svc2021/10/24
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