with reference now to the figures and in particular with reference to fig1 , a pictorial representation of a data processing system in which the present invention may be implemented is depicted in accordance with a preferred embodiment of the present invention . a computer 100 is depicted which includes a system unit 102 , a video display terminal 104 , a keyboard 106 , storage devices 108 , which may include floppy drives and other types of permanent and removable storage media , and mouse 110 . additional input devices may be included with personal computer 100 , such as , for example , a joystick , touchpad , touch screen , trackball , microphone , and the like . computer 100 can be implemented using any suitable computer , such as an ibm rs / 6000 computer or intellistation computer , which are products of international business machines corporation , located in armonk , n . y . although the depicted representation shows a computer , other embodiments of the present invention may be implemented in other types of data processing systems , such as a network computer . computer 100 also preferably includes a graphical user interface that may be implemented by means of systems software residing in computer readable media in operation within computer 100 . with reference now to fig2 , a block diagram of a data processing system is shown in which the present invention may be implemented . data processing system 200 is an example of a computer , such as computer 100 in fig1 , in which code or instructions implementing the processes of the present invention may be located . data processing system 200 employs a peripheral component interconnect ( pci ) local bus architecture . although the depicted example employs a pci bus , other bus architectures such as accelerated graphics port ( agp ) and industry standard architecture ( isa ) may be used . processor 202 and main memory 204 are connected to pci local bus 206 through pci bridge 208 . pci bridge 208 also may include an integrated memory controller and cache memory for processor 202 . additional connections to pci local bus 206 may be made through direct component interconnection or through add - in boards . in the depicted example , local area network ( lan ) adapter 210 , small computer system interface scsi host bus adapter 212 , and expansion bus interface 214 are connected to pci local bus 206 by direct component connection . in contrast , audio adapter 216 , graphics adapter 218 , and audio / video adapter 219 are connected to pci local bus 206 by add - in boards inserted into expansion slots . expansion bus interface 214 provides a connection for a keyboard and mouse adapter 220 , modem 222 , and additional memory 224 . scsi host bus adapter 212 provides a connection for hard disk drive 226 , tape drive 228 , and cd - rom drive 230 . typical pci local bus implementations will support three or four pci expansion slots or add - in connectors . an operating system runs on processor 202 and is used to coordinate and provide control of various components within data processing system 200 in fig2 . the operating system may be a commercially available operating system such as windows 2000 , which is available from microsoft corporation . an object oriented programming system such as java may run in conjunction with the operating system and provides calls to the operating system from java programs or applications executing on data processing system 200 . “ java ” is a trademark of sun microsystems , inc . instructions for the operating system , the object - oriented programming system , and applications or programs are located on storage devices , such as hard disk drive 226 , and may be loaded into main memory 204 for execution by processor 202 . those of ordinary skill in the art will appreciate that the hardware in fig2 may vary depending on the implementation . other internal hardware or peripheral devices , such as flash rom ( or equivalent nonvolatile memory ) or optical disk drives and the like , may be used in addition to or in place of the hardware depicted in fig2 . also , the processes of the present invention may be applied to a multiprocessor data processing system . for example , data processing system 200 , if optionally configured as a network computer , may not include scsi host bus adapter 212 , hard disk drive 226 , tape drive 228 , and cd - rom 230 , as noted by dotted line 232 in fig2 denoting optional inclusion . in that case , the computer , to be properly called a client computer , must include some type of network communication interface , such as lan adapter 210 , modem 222 , or the like . as another example , data processing system 200 may be a stand - alone system configured to be bootable without relying on some type of network communication interface , whether or not data processing system 200 comprises some type of network communication interface . as a further example , data processing system 200 may be a personal digital assistant ( pda ), which is configured with rom and / or flash rom to provide non - volatile memory for storing operating system files and / or user - generated data . the depicted example in fig2 and above - described examples are not meant to imply architectural limitations . for example , data processing system 200 also may be a notebook computer or hand held computer in addition to taking the form of a pda . data processing system 200 also may be a kiosk or a web appliance . the processes of the present invention are performed by processor 202 using computer implemented instructions , which may be located in a memory such as , for example , main memory 204 , memory 224 , or in one or more peripheral devices 226 - 230 . in the preferred embodiment as well as in the claims , a classifier or classification device refers to a device that accepts an input data and produces an output decision using some mapping function . this invention is related to an autonomous classification device , where the autonomy is achieved through automatic configurability , optimization and self healing . in the preferred embodiment , the automatic configurability for the classification device implies the ability of the classification device to configure itself in the environment in which it is expected to operate , configure itself in terms of its operating characteristics based on the requirement of the environment . the continuous optimization of a classification device in the preferred embodiment is achieved through the use of an intrinsic training corpus and evaluation function in conjunction with any extrinsic inputs and supervision provided by the environment and the continuous optimization optimizes a value function such as precision or recall or average precision . the self - healing ability in the preferred embodiment translates into a proactive interaction device that analyzes the autonomous classification device , figures out where and how the classification device is providing inaccurate outputs , or the situation where the mapping function needs to be updated to heal and protect its integrity in terms of performance measure , and is able to proactively seek assistance and guidance from the environment to thus heal itself . we now describe the preferred embodiment using fig1 - 7 . fig3 shows autonomous classification device 300 . the components of autonomous classification device 300 consists of environment sensing and classification configuration device 302 , classification optimization device 304 , proactive interaction device 306 and classification device 308 . autonomous classification device 300 operates in an environment with which it interacts and converts input to be classified 310 into an output 312 that is a decision . the purpose of environment sensing and classification configuration device 302 is to communicate the classification input and output format with the environment 314 , set the configuration of autonomous classification device 300 in congruence with the requirements from the environment . in the preferred embodiment this is done through standard based description of the input , and output definition of the classification device . for example in a preferred embodiment , the classification device could receive as input a 166 dimensional color histogram feature for image classification and the output could be a 3 dimensional feature . fig4 shows classification device 400 . it consists of three components , classification input acceptance device 402 , classification mapping device 404 and classification output delivery device 406 . in a preferred embodiment mapping device 404 could be learnt or provided by the user . also mapping device 404 could be a lookup table or a functional form of the input into the output . fig5 shows environment sensing and classification configuration device 500 , which consists of environment sensing device 502 , input configuration device 504 , output configuration device 506 and mapping configuration device 508 . the environment sensing and classification configuration device interacts with environment 314 to decide how it should operate and how it should automatically configure itself given the environment . fig6 shows classification optimization device 600 , which consists of configuration optimization device 602 , classification evaluation device 604 and optimization training corpus 606 that is used by classification optimization device 606 to optimize classification performance over the input , mapping and output configurations of the classification device and the optimization is validated using the classification evaluation device 604 . in a preferred embodiment the configuration of one or more of the input device , output device and the mapping device could be parametric and the adjustment in the process of autonomous behavior could adjust the parameters of the device ( s ). in a preferred embodiment the self optimization performed by classification optimization device 600 would adjust the parameters of the input , output and mapping device to achieve optimal performance as measured over some goodness metric or function that is calculated by the evaluation device . fig7 shows proactive interaction device 700 which consists of proactive interaction management device 702 , input acceptance device 704 , classification state monitoring device 706 and output monitoring device 708 . in a preferred embodiment the self healing activities of the autonomous classification device 300 is performed by the proactive interaction device 306 which uses the classification device 308 , the evaluation device ( which evaluates the current classifier and determines how well the classifier is doing in terms of its performance measures ) and a proactive interaction management device 306 to seek input / guidance from the environment so as to adapt , improve its performance , correct its errors of configuration , performance and in general heal itself . fig8 shows a precision recall curve that can be a performance characterization method that in a preferred embodiment can be used to configure the autonomous classification device at a particular operating point on the curve based on the requirement of the environment . the same performance characterization method is something that could be optimized by the classification optimization device . finally this performance characterization of the device could be used by the proactive interaction device to seek input from the environment and in the preferred embodiment could be the measure that the self healing process of the proactive interaction device is trying to improve . the self configuration can be performed by using the operating characteristics curves which in a preferred embodiment could be a precision recall curve . the environment could cause the autonomous classification device to operate at a particular operating characteristic in terms of precision and recall . fig9 shows the plot of a goodness measure of the mapping function plotted as a function of the parameters of the mapping function . the classification optimization device could optimize the device operation over input , output and mapping parameters by creating such performance characteristics to calibrate the classification device and then consulting the calibration for self optimization , automatic configuration and healing . for example , in a preferred embodiment the two dimensions could be two different features and the manifold shown in the fig7 is the goodness measure obtained using the classification evaluation device . based on this the autonomous performance functions ( self configuration , self optimization and self healing ) can act . the environment could cause the self configuration of the autonomous classification device to figure out that of the 2 features using the system only one is available and hence the operating characteristics or calibration curves could be used by the device to change the operating point on the curve from the configuration which is optimal for 2 features to the configuration which is optimal for the available feature . the self optimization can be performed by selecting the operating point in fig7 that leads to the highest value of the goodness function . the self healing can be performed by attempting to seek environment input to improve the values of the goodness function at selected operating points . it is important to note that while the present invention has been described in the context of a fully functioning data processing system , those of ordinary skill in the art will appreciate that the processes of the present invention are capable of being distributed in the form of a computer readable medium of instructions and a variety of forms and that the present invention applies equally regardless of the particular type of signal bearing media actually used to carry out the distribution . examples of computer readable media include recordable - type media , such as a floppy disk , a hard disk drive , a ram , cd - roms , and dvd - roms . the computer readable media may take the form of coded formats that are decoded for actual use in a particular data processing system . the description of the present invention has been presented for purposes of illustration and description , and is not intended to be exhaustive or limited to the invention in the form disclosed . many modifications and variations will be apparent to those of ordinary skill in the art . the embodiment was chosen and described in order to best explain the principles of the invention , the practical application , and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated .