Method and system for implementing machine learning classifications

A system comprising:

• one or more hardware processors;
• one or more non-transitory computer-readable media;
• and
• program instructions stored on the one or more non-transitory computer readable media which, when executed by the one or more hardware processors, cause the system to perform operations comprising:
• applying, by a log analytics system configured to analyze log data generated by a computer system, a first machine-learned classifier of a particular classifier type to a set of log data, to obtain a first score for classifying the set of log data as being of a first possible log type of a plurality of possible log types;
• applying, by the log analytics system, a second machine-learned classifier of a different classifier type than the particular classifier type to the set of log data, to obtain a second score for classifying the set of log data as being of the first possible type;
• generating a graphical user interface (GUI) that presents the plurality of possible log types of the set of log data, the GUI comprising visual representations of:
• the first possible log type of the set of log data, of the plurality of possible log types;
• a second possible log type of the set of log data, of the plurality of possible log types;
• wherein the first possible log type and the second possible log type are ordered in the GUI according to their respective probabilities;
• wherein their respective probabilities comprise a probability of the set of log data being of the first possible log type, determined based at least in part on the first score and the second score;
• responsive to receiving, via the GUI, user input selecting the first possible log type of the set of log data:
• applying, by the log analytics system, a log parser associated with the first possible log type to the set of log data.

A method comprising:

• applying, by a log analytics system configured to analyze log data generated by a computer system, a first machine-learned classifier of a particular classifier type to a set of log data, to obtain a first score for classifying the set of log data as being of a first possible log type of a plurality of possible log types;
• applying, by the log analytics system, a second machine-learned classifier of a different classifier type than the particular classifier type to the set of log data, to obtain a second score for classifying the set of log data as being of the first possible log type;
• generating a graphical user interface (GUI) that presents the plurality of possible log types of the set of log data, the GUI comprising visual representations of:
• the first possible log type of the set of log data, of the plurality of possible log types;
• a second possible log type of the set of log data, of the plurality of possible log types;
• wherein the first possible log type and the second possible log type are ordered in the GUI according to their respective probabilities;
• wherein their respective probabilities comprise a probability of the set of log data being of the first possible log type, determined based at least in part on the first score and the second score;
• responsive to receiving, via the GUI, user input selecting the first possible log type of the set of log data:
• applying, by the log analytics system, a log parser associated with the first possible log type to the set of log data;
• wherein the method is performed by at least one device including a hardware processor.