Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying, by executing an instruction with a processor, in the return path data, first tuning data corresponding to a first group of set top boxes, the first group of set top boxes classified as associated with machine events, determining, by executing an instruction with a processor, a ratio between first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of the set top boxes, the second tuning events attributed to a second group of the set top boxes classified at not associated with machine events, and in response to the ratio satisfying a threshold during a time interval, removing second tuning data associated with the time interval from the first tuning data.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying, by executing an instruction with a processor, in the return path data, first tuning data corresponding to a first group of set top boxes, the first group of set top boxes classified as associated with machine events, determining, by executing an instruction with a processor, a ratio between first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of the set top boxes, the second tuning events attributed to a second group of the set top boxes classified at not associated with machine events, and in response to the ratio satisfying a threshold during a time interval, removing second tuning data associated with the time interval from the first tuning data.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying, by executing an instruction with a processor, in the return path data, first tuning data corresponding to a first group of set top boxes, the first group of set top boxes classified as associated with machine events, determining, by executing an instruction with a processor, a ratio between first tuning events in the return path data and second tuning events in the return path data, the first tuning events attributed to the first group of the set top boxes, the second tuning events attributed to a second group of the set top boxes classified at not associated with machine events, and in response to the ratio satisfying a threshold during a time interval, removing second tuning data associated with the time interval from the first tuning data.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying in return path data a first group of set top boxes classified as likely to exhibit machine events in tuning data of the return path data more frequently than a second group of set top boxes represented in the return path data. Additionally, in some examples, the method includes determining whether the first group of set top boxes includes a machine event based on a pattern of the tuning data in the return path data for respective ones of the first group of set top boxes and improving an accuracy of return path data by rectifying the machine event.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying in return path data a first group of set top boxes classified as likely to exhibit machine events in tuning data of the return path data more frequently than a second group of set top boxes represented in the return path data. Additionally, in some examples, the method includes determining whether the first group of set top boxes includes a machine event based on a pattern of the tuning data in the return path data for respective ones of the first group of set top boxes and improving an accuracy of return path data by rectifying the machine event.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying in return path data a first group of set top boxes classified as likely to exhibit machine events in tuning data of the return path data more frequently than a second group of set top boxes represented in the return path data. Additionally, in some examples, the method includes determining whether the first group of set top boxes includes a machine event based on a pattern of the tuning data in the return path data for respective ones of the first group of set top boxes and improving an accuracy of return path data by rectifying the machine event.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to rectify false set top box tuning data. Disclosed examples methods include identifying in return path data a first group of set top boxes classified as likely to exhibit machine events in tuning data of the return path data more frequently than a second group of set top boxes represented in the return path data. Additionally, in some examples, the method includes determining whether the first group of set top boxes includes a machine event based on a pattern of the tuning data in the return path data for respective ones of the first group of set top boxes and improving an accuracy of return path data by rectifying the machine event.