Equipment #21
Words-Cloud visualization:
Note: Missing dates are formatted as ” / /” and missing reports as “” Null string in COGZ.
In the previous report we noted that TFIDF did not serve well enough for grouping the maintenance reports. Instead in this report we are using Dimensional Reduction with TSNA method:
Dimensional Reduction
Click on the image below to interact with CloudNote by running the mouse over the blue dots, each dot is a free form English maintenance record:
Predict Functions
Ensemble of algorithms are computed for predicting the maintenance date and the servers select the most accurate ones and report to the Cloud:
The best algorithm for Equipment #21 was computed to be:
LinearRegression: ±18.8556 days error
Note: To make the prediction more accurate the Δ days predicted for the next upcoming maintenance rather than the absolute date.
Equipment #31
Words-Cloud visualization:
Dimensional Reduction
Click on the image below to interact with CloudNote by running the mouse over the blue dots, each dot is a free form English maintenance record:
Predict Functions
The best algorithm for Equipment #31 was computed to be:
LinearRegression: ±13.5445 days error
Note: To make the prediction more accurate the Δ days predicted for the next upcoming maintenance rather than the absolute date.
Equipment #52
Words-Cloud visualization:
Dimensional Reduction
Click on the image below to interact with CloudNote by running the mouse over the blue dots, each dot is a free form English maintenance record:
Predict Functions
The best algorithm for Equipment #52 was computed to be:
NearestNeighbors: ±20.7334 days error
Note: To make the prediction more accurate the Δ days predicted for the next upcoming maintenance rather than the absolute date.