System and method for monitoring and detecting potential problems early in a VCC based HVAC&R system employs a monitoring application or agent that uses continuous machine learning and a temperature map to derive or “learn” a relation between a measured input power parameter of one or more system compressors, and condenser and evaporator intake fluid temperatures, based on observations of the temperatures and the input power parameter when the HVAC&R system is new or in a “newly maintained” condition. The monitoring agent can then use the learned relation to determine, based on subsequent observations of the condenser and evaporator intake fluid temperatures, the input power parameter values that should be expected if the HVAC&R system were operating in the “newly maintained” condition. The agent can thereafter compare the expected compressor input power parameter values with observed input power parameter values to determine early whether the system is experiencing performance degradation.