| /external/webrtc/webrtc/test/ |
| statistics.cc | 25 double Statistics::Mean() const {
34 return sum_squared_ / count_ - Mean() * Mean();
|
| /external/tensorflow/tensorflow/contrib/eager/python/ |
| metrics_impl.py | 265 class Mean(Metric):
266 """Computes the (weighted) mean of the given values."""
271 super(Mean, self).__init__(name=name)
276 # we make it easier to inherit from Mean().
286 """Accumulate statistics for computing the mean.
288 For example, if values is [1, 3, 5, 7] then the mean is 4.
289 If the weights were specified as [1, 1, 0, 0] then the mean would be 2.
318 class Accuracy(Mean):
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| /external/webrtc/webrtc/modules/audio_processing/vad/ |
| vad_circular_buffer.cc | 48 double VadCircularBuffer::Mean() {
|
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/moment/ |
| Mean.java | 26 * <p>Computes the arithmetic mean of a set of values. Uses the definitional
29 * mean = sum(x_i) / n
42 * <p> If {@link #evaluate(double[])} is used to compute the mean of an array
45 * correcting this by adding the mean deviation of the data values from the
46 * arithmetic mean. See, e.g. "Comparison of Several Algorithms for Computing
59 public class Mean extends AbstractStorelessUnivariateStatistic
76 /** Constructs a Mean. */
77 public Mean() {
83 * Constructs a Mean with an External Moment.
87 public Mean(final FirstMoment m1)
[all...] |
| /frameworks/base/media/mca/filterfw/native/core/ |
| statistics.h | 31 float Mean() const { return mean_; }
|
| /art/libartbase/base/ |
| histogram-inl.h | 141 template <class Value> inline double Histogram<Value>::Mean() const {
197 const TimeUnit unit = GetAppropriateTimeUnit(Mean() * kAdjust);
202 << "Avg: " << FormatDuration(Mean() * kAdjust, unit, kFractionalDigits) << " Max: "
210 os << ": Avg: " << PrettySize(Mean()) << " Max: "
|
| /external/perfetto/src/base/ |
| watchdog_posix.cc | 164 // Add the current stat value to the ring buffer and check that the mean
167 if (memory_window_bytes_.Mean() > memory_limit_bytes_) {
171 memory_window_bytes_.Mean(), memory_limit_bytes_);
218 double Watchdog::WindowedInterval::Mean() const {
|
| /prebuilts/ndk/r16/sources/cxx-stl/llvm-libc++/utils/google-benchmark/src/ |
| stat.h | 110 // Return the mean of this sample set
111 VType Mean() const {
116 // Return the mean of this sample set and compute the standard deviation at
118 VType Mean(VType *stddev) const {
120 VType mean = sum_ * (1.0 / numsamples_);
123 *stddev = Sqrt(avg_squares - Sqr(mean));
125 return mean;
131 VType mean = Mean();
133 return Sqrt(avg_squares - Sqr(mean));
[all...] |
| /external/tensorflow/tensorflow/contrib/lite/toco/tflite/ |
| operator.cc | 549 class Mean : public BuiltinOperator<MeanOperator, ::tflite::MeanOptions,
817 new Mean(::tflite::BuiltinOperator_MEAN, OperatorType::kMean));
[all...] |
| /external/tensorflow/tensorflow/java/src/test/java/org/tensorflow/op/ |
| ScopeTest.java | 164 assertNotNull(g.operation("example/Mean"));
173 assertNotNull(g.operation("variance/Mean"));
228 private static final class Mean<T> {
231 static <T> Mean<T> create(Scope s, Output<T> input, Output<T> reductionIndices) {
232 return new Mean<T>(
234 .opBuilder("Mean", s.makeOpName("Mean"))
241 Mean(Output<T> o) {
302 s.withName("squared_deviation"), x, Mean.create(s, x, zero).output())
305 return new Variance<T>(Mean.create(s.withName("variance"), sqdiff, zero).output())
[all...] |
| /frameworks/base/core/java/com/android/internal/ml/clustering/ |
| KMeans.java | 63 public List<Mean> predict(final int k, final float[][] inputData) {
67 final ArrayList<Mean> means = new ArrayList<>();
69 Mean m = new Mean(dimension);
97 public static double score(@NonNull List<Mean> means) {
101 Mean mean = means.get(i); local
103 Mean compareTo = means.get(j);
104 if (mean == compareTo) {
107 double distance = Math.sqrt(sqDistance(mean.mCentroid, compareTo.mCentroid))
145 final Mean mean = means.get(i); local
157 final Mean mean = means.get(i); local
[all...] |
| /external/apache-commons-math/src/main/java/org/apache/commons/math/stat/descriptive/ |
| SummaryStatistics.java | 24 import org.apache.commons.math.stat.descriptive.moment.Mean;
67 /** SecondMoment is used to compute the mean and variance */
88 /** mean of values that have been added */
89 protected Mean mean = new Mean(); field in class:SummaryStatistics
109 /** Geometric mean statistic implementation - can be reset by setter. */
112 /** Mean statistic implementation - can be reset by setter. */
113 private StorelessUnivariateStatistic meanImpl = mean;
154 // If mean, variance or geomean have been overridden
[all...] |
| /external/tensorflow/tensorflow/go/op/ |
| wrappers.go | [all...] |
