Skip to content

teradataml 17.20.00.05
Compare
Choose a tag to compare
@lcl-teradata lcl-teradata released this 26 Oct 18:04
· 37 commits to main since this release
v17.20.00.05
8144c2a
This commit was created on GitHub.com and signed with GitHub’s verified signature. The key has expired.
GPG key ID: 4AEE18F83AFDEB23
Expired
Learn about vigilant mode.
  • New Features/Functionality
    • teradataml: Hyperparameter-Tuning - Technique to identify best model parameters.

      Hyperparameter tuning is an optimization method to determine the optimal set of
      hyperparameters for the given dataset and learning model. teradataml hyperparameter tuning feature
      offers best model identification, parallel execution, early stopping feature, best data identification,
      model evaluation, model prediction, live logging, input data hyper-parameterization, input data sampling,
      numerous scoring functions, hyper-parameterization for non-model trainer functions.

      • GridSearch
        GridSearch is an exhaustive search algorithm that covers all possible
        parameter values to identify optimal hyperparameters.
        • Methods of GridSearch
          • __init__() - Instantiate an object of GridSearch for given model function and parameters.
          • evaluate() - Function to perform evaluation on the given teradataml DataFrame using default model.
          • fit() - Function to perform hyperparameter-tuning for given hyperparameters and model on teradataml DataFrame.
          • get_error_log() - Useful to get the error log if model execution failed, using the model identifier.
          • get_input_data() - Useful to get the input data using the data identifier, when input data is also parameterized.
          • get_model() - Returns the trained model for the given model identifier.
          • get_parameter_grid() - Returns the hyperparameter space used for hyperparameter optimization.
          • is_running() - Returns the execution status of hyperaparameter tuning.
          • predict() - Function to perform prediction on the given teradataml DataFrame using default model.
          • set_model() - Function to update the default model.
        • Properties of GridSearch
          • best_data_id - Returns the best data identifier used for model training.
          • best_model - Returns the best trained model.
          • best_model_id - Returns the identifier for best model.
          • best_params_ - Returns the best set of hyperparameter.
          • best_sampled_data_ - Returns the best sampled data used to train the best model.
          • best_score_ - Returns the best trained model score.
          • model_stats - Returns the model evaluation reports.
          • models - Returns the metadata of all the models.
      • RandomSearch
        RandomSearch algorithm performs random sampling on hyperparameter
        space to identify optimal hyperparameters.
        • Methods of RandomSearch
          • __init__() - Instantiate an object of RandomSearch for given model function and parameters.
          • evaluate() - Function to perform evaluation on the given teradataml DataFrame using default model.
          • fit() - Function to perform hyperparameter-tuning for given hyperparameters and model on teradataml DataFrame.
          • get_error_log() - Useful to get the error log if model execution failed, using the model identifier.
          • get_input_data() - Useful to get the input data using the data identifier, when input data is also parameterized.
          • get_model() - Returns the trained model for the given model identifier.
          • get_parameter_grid() - Returns the hyperparameter space used for hyperparameter optimization.
          • is_running() - Returns the execution status of hyperaparameter tuning.
          • predict() - Function to perform prediction on the given teradataml DataFrame using default model.
          • set_model() - Function to update the default model.
        • Properties of GridSearch
          • best_data_id - Returns the best data identifier used for model training.
          • best_model - Returns the best trained model.
          • best_model_id - Returns the identifier for best model.
          • best_params_ - Returns the best set of hyperparameter.
          • best_sampled_data_ - Returns the best sampled data used to train the best model.
          • best_score_ - Returns the best trained model score.
          • model_stats - Returns the model evaluation reports.
          • models - Returns the metadata of all the models.
    • teradataml: DataFrame
      • New Functions
        • DataFrame.plot() - Generates the below type of plots on teradataml DataFrame.
          • line - Generates line plot.
          • bar - Generates bar plot.
          • scatter - Generates scatter plot.
          • corr - Generates correlation plot.
          • wiggle - Generates a wiggle plot.
          • mesh - Generates a mesh plot.
        • DataFrame.itertuples() - iterate over teradataml DataFrame rows as namedtuples or list.
    • teradataml: GeoDataFrame
      • New Functions
        • GeoDataFrame.plot() - Generate the below type of plots on teradataml GeoDataFrame.
          • line - Generates line plot.
          • bar - Generates bar plot.
          • scatter - Generates scatter plot.
          • corr - Generates correlation plot.
          • wiggle - Generates a wiggle plot.
          • mesh - Generates a mesh plot.
          • geometry - Generates plot on geospatial data.

    • Plot:

      • Axis - Genertes the axis for plot.
      • Figure - Generates the figure for plot.
      • subplots - Helps in generating multiple plots on a single Figure.

    • Bring Your Own Model (BYOM) Function:

      • DataikuPredict - Score the data in Vantage using the model trained externally in Dataiku UI and stored in Vantage.

    • async_run_status() - Function to check the status of asynchronous run(s) using unique run id(s).

    • teradataml DataFrameColumn a.k.a. ColumnExpression
      • Regular Arithmetic Functions
        • DataFrameColumn.abs() - Computes the absolute value.
        • DataFrameColumn.ceil() - Returns the ceiling value of the column.
        • DataFrameColumn.ceiling() - It is an alias for DataFrameColumn.ceil() function.
        • DataFrameColumn.degrees() - Converts radians value from the column to degrees.
        • DataFrameColumn.exp() - Raises e (the base of natural logarithms) to the power of the value in the column, where e = 2.71828182845905.
        • DataFrameColumn.floor() - Returns the largest integer equal to or less than the value in the column.
        • DataFrameColumn.ln() - Computes the natural logarithm of values in column.
        • DataFrameColumn.log10() - Computes the base 10 logarithm.
        • DataFrameColumn.mod() - Returns the modulus of the column.
        • DataFrameColumn.pmod() - It is an alias for DataFrameColumn.mod() function.
        • DataFrameColumn.nullifzero() - Converts data from zero to null to avoid problems with division by zero.
        • DataFrameColumn.pow() - Computes the power of the column raised to expression or constant.
        • DataFrameColumn.power() - It is an alias for DataFrameColumn.pow() function.
        • DataFrameColumn.radians() - Converts degree value from the column to radians.
        • DataFrameColumn.round() - Returns the rounded off value.
        • DataFrameColumn.sign() - Returns the sign.
        • DataFrameColumn.signum() - It is an alias for DataFrameColumn.sign() function.
        • DataFrameColumn.sqrt() - Computes the square root of values in the column.
        • DataFrameColumn.trunc() - Provides the truncated value of columns.
        • DataFrameColumn.width_bucket() - Returns the number of the partition to which column is assigned.
        • DataFrameColumn.zeroifnull() - Converts data from null to zero to avoid problems with null.
      • Trigonometric Functions
        • DataFrameColumn.acos() - Returns the arc-cosine value.
        • DataFrameColumn.asin() - Returns the arc-sine value.
        • DataFrameColumn.atan() - Returns the arc-tangent value.
        • DataFrameColumn.atan2() - Returns the arc-tangent value based on x and y coordinates.
        • DataFrameColumn.cos() - Returns the cosine value.
        • DataFrameColumn.sin() - Returns the sine value.
        • DataFrameColumn.tan() - Returns the tangent value.
      • Hyperbolic Functions
        • DataFrameColumn.acosh() - Returns the inverse hyperbolic cosine value.
        • DataFrameColumn.asinh() - Returns the inverse hyperbolic sine value.
        • DataFrameColumn.atanh() - Returns the inverse hyperbolic tangent value.
        • DataFrameColumn.cosh() - Returns the hyperbolic cosine value.
        • DataFrameColumn.sinh() - Returns the hyperbolic sine value
        • DataFrameColumn.tanh() - Returns the hyperbolic tangent value.
      • String Functions
        • DataFrameColumn.ascii() - Returns the decimal representation of the first character in column.
        • DataFrameColumn.char2hexint() - Returns the hexadecimal representation for a character string in a column.
        • DataFrameColumn.chr() - Returns the Latin ASCII character of a given a numeric code value in column.
        • DataFrameColumn.char() - It is an alias for DataFrameColumn.chr() function.
        • DataFrameColumn.character_length() - Returns the number of characters in the column.
        • DataFrameColumn.char_length() - It is an alias for DataFrameColumn.character_length() function.
        • DataFrameColumn.edit_distance() - Returns the minimum number of edit operations required to
          transform string in a column into string specified in argument.
        • DataFrameColumn.index() - Returns the position of a string in a column where string specified in argument starts.
        • DataFrameColumn.initcap() - Modifies a string column and returns the string with the first character
          of each word in uppercase.
        • DataFrameColumn.instr() - Searches the string in a column for occurrences of search string passed as argument.
        • DataFrameColumn.lcase() - Returns a character string identical to string values in column,
          with all uppercase letters replaced with their lowercase equivalents.
        • DataFrameColumn.left() - Truncates string in a column to a specified number of characters desired from
          the left side of the string.
        • DataFrameColumn.length() - It is an alias for DataFrameColumn.character_length() function.
        • DataFrameColumn.levenshtein() - It is an alias for DataFrameColumn.edit_distance() function.
        • DataFrameColumn.locate() - Returns the position of the first occurrence of a string in a column within
          string in argument.
        • DataFrameColumn.lower() - It is an alias for DataFrameColumn.character_lcase() function.
        • DataFrameColumn.lpad() - Returns the string in a column padded to the left with the characters specified
          in argument so that the resulting string has length specified in argument.
        • DataFrameColumn.ltrim() - Returns the string in a column, with its left-most characters removed up
          to the first character that is not in the string specified in argument.
        • DataFrameColumn.ngram() - Returns the number of n-gram matches between string in a column,
          and string specified in argument.
        • DataFrameColumn.nvp() - Extracts the value of a name-value pair where the name in the pair matches
          the name and the number of the occurrence specified.
        • DataFrameColumn.oreplace() - Replaces every occurrence of search string in the column.
        • DataFrameColumn.otranslate() - Returns string in a column with every occurrence of each character in
          string in argument replaced with the corresponding character in another argument.
        • DataFrameColumn.replace() - It is an alias for DataFrameColumn.oreplace() function.
        • DataFrameColumn.reverse() - Returns the reverse of string in column.
        • DataFrameColumn.right() - Truncates input string to a specified number of characters desired from
          the right side of the string.
        • DataFrameColumn.rpad() - Returns the string in a column padded to the right with the characters specified
          in argument so the resulting string has length specified in argument.
        • DataFrameColumn.rtrim() - Returns the string in column, with its right-most characters removed up
          to the first character that is not in the string specified in argument.
        • DataFrameColumn.soundex() - Returns a character string that represents the Soundex code for
          string in a column.
        • DataFrameColumn.string_cs() - Returns a heuristically derived integer value that can be used to determine
          which KANJI1-compatible client character set was used to encode string in a column.
        • DataFrameColumn.translate() - It is an alias for DataFrameColumn.otranslate() function.
        • DataFrameColumn.upper() - Returns a character string with all lowercase letters in a column replaced
          with their uppercase equivalents.
    • teradataml Options
      • Configuration Options
        • configure.indb_install_location
          Specifies the installation location of In-DB Python package.
  • Updates
    • Open Analytics Framework (OpenAF) APIs:
      • set_auth_token()
        • set_auth_token() does not accept username and password anymore. Instead, function opens up a browser session and user should authenticate in browser.
        • After token expiry, teradataml will open a browser and user needs to authenticate again.
        • If client machine does not have browser, then user should copy the URL posted by teradataml and authenticate themselves.
      • Security fixes - auth_token is not set or retrieved from the configure option anymore.
      • Manage all user environments.
        • create_env() - supports creation of R environment.
        • remove_env() - Supports removal of remote R environment.
        • remove_all_envs() - Supports removal of all remote R environments.
        • remove_env() and remove_all_envs() supports asynchronous call.
      • UserEnv Class – Supports managing of R remote environments.
        • Properties:
          • libs - Supports listing of libraries in R remote environment.
        • Methods:
          • install_lib() - Supports installing of libraries in remote R environment.
          • uninstall_lib() - Supports uninstalling of libraries in remote R environment.
          • update_lib() - Supports updating of libraries in remote R environment.
    • Unbounded Array Framework (UAF) Functions:
      • ArimaEstimate()
        • Added support for CSS algorithm via algorithm argument.
  • Bug Fixes
    • Installation location of In-DB 2.0.0 package is changed. Script() will now work with both 2.0.0 and previous version.
Assets 3
Loading