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True or False The C4.5 algorithm uses the Gini index as the evaluation criteria for node classification. o 



True False



For data with two dimensions, when k-means is used for clustering, the clustering result is displayed as a sphere in the space.  o



True False



Principal component analysis (PCA) can greatly reduce the data dimension when most information of the original dataset is contained.  o



True False



In Python, the title() function can capitalize the initial letter of a string.  o



True False



In Python, when an object is deleted, the destructor function is automatically called.  o



True False



In Python, multiple inheritance is supported during class definition.  o



True False



In Python, static variables and static methods are instances. o 



True False



Convolutional neural network (CNN) can only be used to solve visual problems and cannot be used for natural language processing. o 



True False



Support vector machine (SVM) has a good effect in dealing with high-dimensional nonlinear problems.  o



True False



If the number of layers of a neural network is too large, gradient disappearance or gradient explosion may occur.  o



True False



Multiple Choice Single Answer. The data output by binary classification can be considered as a probability value. Generally, a threshold is set, for example, 0.5. If the value is greater than the threshold, it is a positive category. Otherwise, it is a negative category. If the threshold is increased from 0.5 to 0.7, which of the following changes will occur in the precision and recall rate of the model? A. The precision increases or remains unchanged, and the recall rate increases or remains unchanged. B. The precision increases or remains unchanged, and the recall rate decreases or remains unchanged. C. The precision decreases or remains unchanged, and the recall rate increases or remains unchanged. D. The precision decreases or remains unchanged, and the recall rate decreases or remains unchanged.



Which of the following assumptions can be made about linear regression? A. It is important to find outliers because linear regression is sensitive to outliers. B. Linear regression requires that all variables be in normal distribution. C. Linear regression assumes that data does not have multiple linear correlations. D. None of the above



Which of the following procedures is not a procedure for building a decision tree? A. Feature selection B. Decision tree generation C. Finding the support vector D. Pruning



When decision tree is used for classification, if the value of an input feature is continuous, the dichotomy is used to discretize the continuous attribute. It means that the classification is performed based on whether the value is greater than or less than a threshold. If the multi-path division is used, each value is divided into a branch. What is the biggest problem of this method? A. The computing workload is too heavy. B. The performance of both the training set and the test set is poor. C. The performance of the training set is good, but the performance of the test set is poor. D. The performance of the training set is poor, and the performance of the test set is good.



For a dataset with only one dependent variable x, what is the number of coefficient(s) required to construct a simplest linear regression model? A. 1 B. 2 C. 3 D. 4



Which of the following algorithms is not an ensemble algorithm? A. XGBoost B. GBDT C. Random forest D. Support vector machine (SVM)



Assume that a classification model is built using logistic regression to obtain the accuracy of training samples and test samples. Then, add a new feature to the data, keep other features unchanged, and train the model again. Which of the following statement is true? A. The accuracy of training samples will definitely decrease. B. The accuracy of test samples will definitely decrease. C. The accuracy of training samples remains unchanged or increases. D. The accuracy of test samples remains unchanged or increases.



About the values of four variables a, b, c, and d after executing the following code, which of the following statements is false? import copy a = [1, 2, 3, 4, [‘a’,’b’] b=a c = copy.copy(a) d = copy.deepcopy(a) a.append(5) a[4].append(‘c’) A. a == [1,2,3,4,[‘a’,’b’,’c’],5] B. b == [1,2,3,4,[‘a’,’b’,’c’],5] C. c == [1,2,3,4,[‘a’,’b’,’c’]] D. d == [1,2,3,4,[‘a’,’b’,’c’]]



The syntax of string formatting is ? A. GNU\’s Not %s %%’ % ’UNIX’ B. ‘GNU\’s Not %d %%’ % ’UNIX’ C. ‘GNU’s Not %s %%’ % ’UNIX’ D. ‘GNU’s Not %d %%’ % ’UNIX’



Which of the following statements about a neural network is true? A. Increasing the number of neural network layers may increase the classification error rate of a test set. B. Reducing the number of neural network layers can always reduce the classification error rate of a test set. C. Increasing the number of neural network layers can always reduce the classification error rate of a training set. D. The neural network can fully fit all data



For a multi-layer perceptron (MLP), the number of nodes at the input layer is 10, and the number of nodes at the hidden layer is 5. The maximum number of connections from the input layer to the hidden layer is? A. It depends on the situation. B. Less than 50 C. Equal to 50 D. Greater than 50



Assume that there is a trained deep neural network model for identifying cats and dogs, and now this model will be used to detect the locations of cats in a new dataset. Which of the following statements is true? A. Retrain the existing model using a new dataset. B. Remove the last layer of the network and retrain the existing model. C. Adjust the last several layers of the network and change the last layer to the regression layer. D. None of the above



If you want to predict the probability of n classes (p1, p2, …, pk), and the sum of probabilities of n classes is equal to 1, which of the following functions can be used as the activation function in the output layer? A. softmax B. ReLu C. sigmoid D. tanh



In which case can a neural network model be called a deep learning model? A. When more layers are added to the network B. When data with higher dimensions is used C. When the model is used for image classification D. None of the above



Which of the following statements about the PyTorch features is false? A. PyTorch uses the dynamic graph. B. Pytorch provides tensors that support CPUs and GPUs C. PyTorch-based code debugging is more difficult than TensorFlow1.x. D. Python first



During the training of a convolutional neural network (CNN), it is often found that the precision of a model in a test set gradually increases as the number of parameter increases. However, when a certain value is reached, the precision decreases. What is the cause of this phenomenon? A. Although the number of convolutional kernel increases, only a small number of convolutional kernels participate in the prediction. B. When the number of convolutional kernels increases, the prediction capability of the neural network decreases. C. When the number of convolutional kernels increases, overfitting will occur. D. None of the above.



When data is too large to be processed at the same time in the RAM, which of the following gradient descent methods is more effective? A. Stochastic gradient descent B. Full batch gradient descent C. Both A and B D. Neither A nor B



To resolve an image recognition problem, such as finding out a cat in a photo, which of the following neural networks offers the best solution? A. Perceptron B. Multi-layer perceptron (MLP) C. Recurrent neural network (RNN) D. Convolutional neural network (CNN)



Multiple Choice Multiple Answer Which of the following activation functions can be used for image classification at the output layer? A. sigmoid B. tanh C. ReLu D. Piecewise functions



Which of the following assumptions are used to derive linear regression parameters? A. There is a linear relationship between independent variables and dependent variables B. Model errors are independent in statistics C. The error generally obeys the normal distribution of 0 and the standard deviation of the fixed average value D. The independent variable is non-random and has no measurement error.



Which of the following operations belong to the data cleansing process? A. B. C. D.



Processing lost data Processing abnormal values Obtaining data that is difficult to be obtained by others through special channels Combining data



Which of the following statements about the convolutional neural network (CNN) are true? A. Increasing the size of convolutional kernels can significantly improve the performance of the CNN. B. Pooling layers in the CNN keep translation invariance. C. Data features need to be extracted before using a CNN. D. In a CNN, the convolutional kernel at each layer is the weight to be learned.



The core idea of convolutional neural network (CNN) are? A. Mainly for image data processing B. Local receptive field C. Parameter sharing D. High-quality data input and high-quality output



Which of the following issues need to be considered when you select the depth of a neural network? A. Neural network types B. Input data type and quantity C. Learning rate



D. Development framework to be used



Which of the following statements about long short-term memory (LSTM) are true? A. The forget phase of LSTM is to selectively forget the input transferred from the previous node. B. The selective memory phase of LSTM is to selectively memorize the input. C. The update phase of LSTM is to update the memory information. D. The output phase of LSTM is to determine which will be considered as the output of current state.



Which of the following statements about TensorFlow 2.0 are true? A. TensorFlow 2.0 requires the construction of a computational graph at first, then you can start a session, import data to the session, and perform training. B. Eager execution is enabled in TensorFlow 2.0 by default. It is a type of command line programming, making the execution simpler. C. In TensorFlow 2.0, if you want to build a new layer, you can directly inherit tf.keras.layers.Layer D. In the default mode of TensorFlow 2.0, tf.data.Dataset is an iterator.



Which of the following statements about the application of deep learning methods are true? A. Massive discrete data can be encoded using embedded mode as input of the neural network, which greatly improves the effect of data analysis. B. The convolutional neural network (CNN) is well applied in the field of image processing, but it cannot be used in natural language processing. C. The recurrent neural network (RNN) is mainly used to deal with sequence-to-sequence problems, but it often encounters the problems of gradient disappearance and gradient explosion. D. The generative adversarial network (GAN) is a method used for model generation.



If data = (1, 3, 5, 7, 9, 11), which of the following operations are valid? A. data[1 : -1] B. data[1 : 7] C. list(data) D. data * 3



If there is a = range(100), which of the following operations are valid? A. a[-1] B. a[2 : 99] C. a[ : - 1 : 2] D. a[5 - 7]



Data cleansing is to clear dirty data in a dataset. The dirty data refers to? A. Data that is stored in the devices affected by some pollutants. B. Data that contains incorrect records or exceptions C. Data that contains contradictory and inconsistent records D. Data that lacks some features or contains some missing values



Features selection is necessary before model training. Which of the following statements are the advantages of feature selection? A. It can improve model generalization and avoid overfitting. B. It can reduce the time required for model training. C. It can avoid dimension explosion. D. It can simplify models to make them easy for users to interpret.



Which of the following operations belong to the data cleansing process? A. Processing lost data B. Processing abnormal values C. Obtaining data that is difficult to be obtained by others through special channels D. Combining data



Which of the following assumptions are used to derive linear regression parameters? A. There is a linear relationship between independent variables and dependent variables B. Model errors are independent in statistics. C. The error generally obeys the normal distribution of 0 and the standard deviation of the fixed average value. D. The independent variable is non-random and has no measurement error.



Principal component analysis (PCA) is a common and effective method for dimensionality reduction. Which of the following statements about PCA are true? A. Before using PCA, data standardization is required. B. Before using PCA, data standardization is not required. C. The principal component with the maximum variance should be selected. D. The principal component with the minimum variance should be selected.



When the parameters are the same in all cases, and how does the number of sample observation times affect overfitting? A. The number of observation times is small, and overfitting is likely to occur. B. The number of observation times is small, and overfitting is not likely to occur. C. The number of observation times is large, and overfitting is likely to occur. D. The number of observation times is large, and overfitting is not likely to occur



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Which of the following statements about strings is false?



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Which of the following statements is invalid in Python?



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The data output by binary classification can be considered as a probability value. Generally, a threshold is set, for example, 0.5. If the value is greater than the threshold, it is a positive category. Otherwise, it is a negative category. If the threshold is increased from 0.5 to 0.7, which of the following changes will occur in the precision and recall rate of the model?