Data Preprocessing: Missing Data Techniques
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Questions and Answers

Which philosopher is known for developing mathematical logic in the 17th-19th century?

  • Karl Popper
  • Arthur Schopenhauer
  • Gottfried Wilhelm Leibniz (correct)
  • Isaac Newton

    • What event is considered the official birth of the field of Artificial Intelligence?

  • The Dartmouth Conference (correct)
  • The AI Winter
  • The Turing Test
  • The first AI symposium

    • What was one major outcome of the AI Winter in the late 1970s?

  • Increased public interest in AI technologies
  • Development of advanced machine learning algorithms
  • The rise of neural networks
  • Reduced funding and interest in AI research (correct)

    • What foundational goal for AI was proposed by Alan Turing in the 1950s?

    <p>To mimic human intelligence</p> Signup and view all the answers

    During the period from the 1960s to the 1970s, which of the following was a significant achievement of early AI research?

    <p>Creating programs that could engage in conversational language</p> Signup and view all the answers

    Which one of the following reflects a misunderstanding of the goals of early AI research?

    <p>The goal was to develop only narrow or specialized AI.</p> Signup and view all the answers

    Which event signified an early success in AI during the 1960s?

    <p>The development of English-speaking programs</p> Signup and view all the answers

    What was Alan Turing’s contribution to the field of AI?

    <p>He proposed the Turing Test for assessing machine intelligence.</p> Signup and view all the answers

    What significant development in AI occurred during the 1980s?

    <p>Commercial success of expert systems</p> Signup and view all the answers

    Which technology saw a significant shift in focus during the 1990s?

    <p>Machine learning</p> Signup and view all the answers

    What was a major factor that contributed to AI's advancements in the 2000s?

    <p>Explosion of data on the internet</p> Signup and view all the answers

    Which of the following was crucial for advancements in neural networks in the 1990s?

    <p>Invention of backpropagation algorithm</p> Signup and view all the answers

    What characterizes the AI landscape from 2010 to the present?

    <p>Mainstream adoption in everyday technology</p> Signup and view all the answers

    In which decade did AI experience a resurgence due to commercial success?

    <p>1980s</p> Signup and view all the answers

    How did the role of data change as AI progressed into the 2000s?

    <p>Data availability peaked and enhanced AI capabilities</p> Signup and view all the answers

    Which area of AI saw breakthroughs specifically in image and speech recognition during the 2000s?

    <p>Deep learning</p> Signup and view all the answers

    Which event marked a significant achievement in AI by IBM?

    <p>Watson wins Jeopardy!</p> Signup and view all the answers

    Which of the following strategies can SimpleImputer use to replace missing values?

    <p>mean</p> Signup and view all the answers

    What ethical considerations are growing concerns as AI becomes more integrated into society?

    <p>Privacy and autonomy</p> Signup and view all the answers

    In what year did Google acquire DeepMind?

    <p>2014</p> Signup and view all the answers

    What is the default value for the 'missing_values' parameter in SimpleImputer?

    <p>None</p> Signup and view all the answers

    What major advancement is exemplified by the systems developed by OpenAI?

    <p>Natural language processing</p> Signup and view all the answers

    Which parameter in SimpleImputer determines the strategy for handling missing data?

    <p>strategy</p> Signup and view all the answers

    Which AI milestone involved DeepMind's AlphaGo?

    <p>Defeating a world champion in Go</p> Signup and view all the answers

    What does the 'most_frequent' method do in SimpleImputer?

    <p>Replaces missing values with the most frequent value in the column.</p> Signup and view all the answers

    What is the purpose of the fit_transform method in scikit-learn?

    <p>To fit the transformer and transform the dataset in a single step.</p> Signup and view all the answers

    What does the ColumnTransformer class do?

    <p>Allows application of different transformers to different columns.</p> Signup and view all the answers

    Which statement correctly describes the role of LabelEncoder?

    <p>It encodes target variables into a numerical format.</p> Signup and view all the answers

    What does the 'remainder="passthrough"' option in ColumnTransformer specify?

    <p>Columns not specified will remain unchanged.</p> Signup and view all the answers

    When should scaling be applied in the data processing pipeline?

    <p>Before splitting the dataset to avoid data leakage.</p> Signup and view all the answers

    What is the result of the np.array(...) conversion mentioned?

    <p>Converts the transformed result into a NumPy array.</p> Signup and view all the answers

    What does the transform(X) method of SimpleImputer do?

    <p>It replaces missing values in the dataset using the imputation strategy.</p> Signup and view all the answers

    Study Notes

    Data Preprocessing: Missing Data

    • The SimpleImputer class in scikit-learn handles missing data.
    • missing_values (default=None): Specifies values treated as missing. Uses np.nan if left as None.
    • strategy (default='mean'): Imputation strategy:
      • 'mean': Replaces with the mean of the column's non-missing values.
      • 'median': Replaces with the median of the column's non-missing values.
      • 'most_frequent': Replaces with the most frequent value in the column.
      • 'constant': Replaces with a constant specified by the fill_value parameter.

    Data Preprocessing: SimpleImputer Methods

    • fit(X): Computes the mean, median, most frequent value, or constant based on the strategy.
    • transform(X): Replaces missing values with the values calculated during fit().

    Data Preprocessing: Encoding the Independent Variable

    • ColumnTransformer: Applies specific transformations to different columns of a dataset.
    • OneHotEncoder: Converts categorical variables into a binary matrix, known as one-hot encoding.
    • remainder='passthrough': Leaves columns not specified in the transformations unchanged.
    • fit_transform: Fits the transformer to the dataset X and transforms it in one step.

    Data Preprocessing: Encoding the Dependent Variable

    • LabelEncoder: Encodes labels (target variable) into numerical format.
    • fit_transform: Fits the encoder to the unique values and transforms the labels into numbers.

    Data Preprocessing: Splitting the Dataset

    • The train_test_split function splits the dataset into training and testing sets.

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    Related Documents

    F of ML_Part_1.pdf

    Description

    This quiz explores various techniques for handling missing data using the SimpleImputer class in scikit-learn. It covers the imputation strategies available, including mean, median, most frequent, and constant. Additionally, the methods fit() and transform() will be discussed, highlighting their roles in data preprocessing.

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